├── AUTHORS.txt ├── LICENSE.txt ├── README.md ├── data ├── australia │ ├── README │ ├── SUA_LatLong.xlsx │ ├── SUA_association_2016_2021.xlsx │ ├── __init__.py │ ├── aus_sua_pop.csv │ ├── historical_pop.csv │ ├── raw_data │ │ ├── age-by-SUA.csv │ │ ├── educationLevel-SUA.csv │ │ └── income-by-SUA.csv │ └── top2021.csv ├── brazil │ ├── Readme.me │ ├── __init__.py │ ├── __pycache__ │ │ ├── __init__.cpython-36.pyc │ │ ├── __init__.cpython-38.pyc │ │ ├── data.cpython-36.pyc │ │ └── data.cpython-38.pyc │ ├── data.py │ ├── json │ │ ├── data-GDP2010.json │ │ ├── data-aids2010.json │ │ └── data-externalCauses2010.json │ └── raw_data │ │ ├── aids-1996-2012.dat │ │ ├── aids-1996-2012.txt │ │ ├── externalCauses-1996-2012.dat │ │ ├── externalCauses-1996-2012.txt │ │ ├── gdp-2000-2012.dat │ │ ├── gdp-2000-2012.txt │ │ ├── population-1996-2012.dat │ │ ├── population-1996-2012.dat~ │ │ ├── population-1996-2012.txt │ │ └── spatial.csv ├── covid19 │ ├── .DS_Store │ ├── Readme.me │ ├── __init__.py │ ├── __pycache__ │ │ └── __init__.cpython-38.pyc │ ├── _covid19_preprocessing │ │ ├── .ipynb_checkpoints │ │ │ ├── A0_Data_preprocessing-checkpoint.ipynb │ │ │ ├── A1_Data_preprocessing_with_dates-checkpoint.ipynb │ │ │ └── A2_Create_fitting_file-checkpoint.ipynb │ │ ├── A0_Data_preprocessing.ipynb │ │ ├── A1_Data_preprocessing_with_dates.ipynb │ │ └── A2_Create_fitting_file.ipynb │ ├── _generated_files │ │ ├── .DS_Store │ │ ├── AllScales24Oct.pkl │ │ ├── All_Pop_Zipf.png │ │ ├── Brazil24Oct.csv │ │ ├── Brazil_by_dates │ │ │ ├── .DS_Store │ │ │ ├── Brazil_105.txt │ │ │ ├── Brazil_115.txt │ │ │ ├── Brazil_125.txt │ │ │ ├── Brazil_135.txt │ │ │ ├── Brazil_145.txt │ │ │ ├── Brazil_155.txt │ │ │ ├── Brazil_165.txt │ │ │ ├── Brazil_175.txt │ │ │ ├── Brazil_185.txt │ │ │ ├── Brazil_195.txt │ │ │ ├── Brazil_205.txt │ │ │ ├── Brazil_215.txt │ │ │ ├── Brazil_225.txt │ │ │ ├── Brazil_235.txt │ │ │ ├── Brazil_245.txt │ │ │ ├── Brazil_25.txt │ │ │ ├── Brazil_255.txt │ │ │ ├── Brazil_265.txt │ │ │ ├── Brazil_275.txt │ │ │ ├── Brazil_285.txt │ │ │ ├── Brazil_295.txt │ │ │ ├── Brazil_30.txt │ │ │ ├── Brazil_300.txt │ │ │ ├── Brazil_310.txt │ │ │ ├── Brazil_320.txt │ │ │ ├── Brazil_330.txt │ │ │ ├── Brazil_340.txt │ │ │ ├── Brazil_35.txt │ │ │ ├── Brazil_350.txt │ │ │ ├── Brazil_360.txt │ │ │ ├── Brazil_370.txt │ │ │ ├── Brazil_38.txt │ │ │ ├── Brazil_380.txt │ │ │ ├── Brazil_390.txt │ │ │ ├── Brazil_400.txt │ │ │ ├── Brazil_410.txt │ │ │ ├── Brazil_420.txt │ │ │ ├── Brazil_430.txt │ │ │ ├── Brazil_440.txt │ │ │ ├── Brazil_45.txt │ │ │ ├── Brazil_450.txt │ │ │ ├── Brazil_460.txt │ │ │ ├── Brazil_470.txt │ │ │ ├── Brazil_480.txt │ │ │ ├── Brazil_490.txt │ │ │ ├── Brazil_55.txt │ │ │ ├── Brazil_65.txt │ │ │ ├── Brazil_75.txt │ │ │ ├── Brazil_85.txt │ │ │ ├── Brazil_95.txt │ │ │ └── _results │ │ │ │ ├── .DS_Store │ │ │ │ ├── Betas_Brazil.png │ │ │ │ ├── results_Brazil_105.pickle │ │ │ │ ├── results_Brazil_115.pickle │ │ │ │ ├── results_Brazil_125.pickle │ │ │ │ ├── results_Brazil_135.pickle │ │ │ │ ├── results_Brazil_145.pickle │ │ │ │ ├── results_Brazil_155.pickle │ │ │ │ ├── results_Brazil_165.pickle │ │ │ │ ├── results_Brazil_175.pickle │ │ │ │ ├── results_Brazil_185.pickle │ │ │ │ ├── results_Brazil_195.pickle │ │ │ │ ├── results_Brazil_205.pickle │ │ │ │ ├── results_Brazil_215.pickle │ │ │ │ ├── results_Brazil_225.pickle │ │ │ │ ├── results_Brazil_235.pickle │ │ │ │ ├── results_Brazil_245.pickle │ │ │ │ ├── results_Brazil_25.pickle │ │ │ │ ├── results_Brazil_255.pickle │ │ │ │ ├── results_Brazil_265.pickle │ │ │ │ ├── results_Brazil_275.pickle │ │ │ │ ├── results_Brazil_285.pickle │ │ │ │ ├── results_Brazil_295.pickle │ │ │ │ ├── results_Brazil_30.pickle │ │ │ │ ├── results_Brazil_300.pickle │ │ │ │ ├── results_Brazil_310.pickle │ │ │ │ ├── results_Brazil_320.pickle │ │ │ │ ├── results_Brazil_330.pickle │ │ │ │ ├── results_Brazil_340.pickle │ │ │ │ ├── results_Brazil_35.pickle │ │ │ │ ├── results_Brazil_350.pickle │ │ │ │ ├── results_Brazil_360.pickle │ │ │ │ ├── results_Brazil_370.pickle │ │ │ │ ├── results_Brazil_38.pickle │ │ │ │ ├── results_Brazil_380.pickle │ │ │ │ ├── results_Brazil_390.pickle │ │ │ │ ├── results_Brazil_400.pickle │ │ │ │ ├── results_Brazil_410.pickle │ │ │ │ ├── results_Brazil_420.pickle │ │ │ │ ├── results_Brazil_430.pickle │ │ │ │ ├── results_Brazil_440.pickle │ │ │ │ ├── results_Brazil_45.pickle │ │ │ │ ├── results_Brazil_450.pickle │ │ │ │ ├── results_Brazil_460.pickle │ │ │ │ ├── results_Brazil_470.pickle │ │ │ │ ├── results_Brazil_480.pickle │ │ │ │ ├── results_Brazil_490.pickle │ │ │ │ ├── results_Brazil_55.pickle │ │ │ │ ├── results_Brazil_60.pickle │ │ │ │ ├── results_Brazil_65.pickle │ │ │ │ ├── results_Brazil_70.pickle │ │ │ │ ├── results_Brazil_75.pickle │ │ │ │ ├── results_Brazil_80.pickle │ │ │ │ ├── results_Brazil_85.pickle │ │ │ │ ├── results_Brazil_95.pickle │ │ │ │ ├── x_Brazil_105.pickle │ │ │ │ ├── x_Brazil_115.pickle │ │ │ │ ├── x_Brazil_125.pickle │ │ │ │ ├── x_Brazil_135.pickle │ │ │ │ ├── x_Brazil_145.pickle │ │ │ │ ├── x_Brazil_155.pickle │ │ │ │ ├── x_Brazil_165.pickle │ │ │ │ ├── x_Brazil_175.pickle │ │ │ │ ├── x_Brazil_185.pickle │ │ │ │ ├── x_Brazil_195.pickle │ │ │ │ ├── x_Brazil_205.pickle │ │ │ │ ├── x_Brazil_215.pickle │ │ │ │ ├── x_Brazil_225.pickle │ │ │ │ ├── x_Brazil_235.pickle │ │ │ │ ├── x_Brazil_245.pickle │ │ │ │ ├── x_Brazil_25.pickle │ │ │ │ ├── x_Brazil_255.pickle │ │ │ │ ├── x_Brazil_265.pickle │ │ │ │ ├── x_Brazil_275.pickle │ │ │ │ ├── x_Brazil_285.pickle │ │ │ │ ├── x_Brazil_295.pickle │ │ │ │ ├── x_Brazil_30.pickle │ │ │ │ ├── x_Brazil_300.pickle │ │ │ │ ├── x_Brazil_310.pickle │ │ │ │ ├── x_Brazil_320.pickle │ │ │ │ ├── x_Brazil_330.pickle │ │ │ │ ├── x_Brazil_340.pickle │ │ │ │ ├── x_Brazil_35.pickle │ │ │ │ ├── x_Brazil_350.pickle │ │ │ │ ├── x_Brazil_360.pickle │ │ │ │ ├── x_Brazil_370.pickle │ │ │ │ ├── x_Brazil_380.pickle │ │ │ │ ├── x_Brazil_38pickle │ │ │ │ ├── x_Brazil_390.pickle │ │ │ │ ├── x_Brazil_400.pickle │ │ │ │ ├── x_Brazil_410.pickle │ │ │ │ ├── x_Brazil_420.pickle │ │ │ │ ├── x_Brazil_430.pickle │ │ │ │ ├── x_Brazil_440.pickle │ │ │ │ ├── x_Brazil_45.pickle │ │ │ │ ├── x_Brazil_450.pickle │ │ │ │ ├── x_Brazil_460.pickle │ │ │ │ ├── x_Brazil_470.pickle │ │ │ │ ├── x_Brazil_480.pickle │ │ │ │ ├── x_Brazil_490.pickle │ │ │ │ ├── x_Brazil_55.pickle │ │ │ │ ├── x_Brazil_60.pickle │ │ │ │ ├── x_Brazil_65.pickle │ │ │ │ ├── x_Brazil_70.pickle │ │ │ │ ├── x_Brazil_75.pickle │ │ │ │ ├── x_Brazil_80.pickle │ │ │ │ ├── x_Brazil_85.pickle │ │ │ │ ├── x_Brazil_95.pickle │ │ │ │ ├── y_Brazil_105.pickle │ │ │ │ ├── y_Brazil_115.pickle │ │ │ │ ├── y_Brazil_125.pickle │ │ │ │ ├── y_Brazil_135.pickle │ │ │ │ ├── y_Brazil_145.pickle │ │ │ │ ├── y_Brazil_155.pickle │ │ │ │ ├── y_Brazil_165.pickle │ │ │ │ ├── y_Brazil_175.pickle │ │ │ │ ├── y_Brazil_185.pickle │ │ │ │ ├── y_Brazil_195.pickle │ │ │ │ ├── y_Brazil_205.pickle │ │ │ │ ├── y_Brazil_215.pickle │ │ │ │ ├── y_Brazil_225.pickle │ │ │ │ ├── y_Brazil_235.pickle │ │ │ │ ├── y_Brazil_245.pickle │ │ │ │ ├── y_Brazil_25.pickle │ │ │ │ ├── y_Brazil_255.pickle │ │ │ │ ├── y_Brazil_265.pickle │ │ │ │ ├── y_Brazil_275.pickle │ │ │ │ ├── y_Brazil_285.pickle │ │ │ │ ├── y_Brazil_295.pickle │ │ │ │ ├── y_Brazil_30.pickle │ │ │ │ ├── y_Brazil_300.pickle │ │ │ │ ├── y_Brazil_310.pickle │ │ │ │ ├── y_Brazil_320.pickle │ │ │ │ ├── y_Brazil_330.pickle │ │ │ │ ├── y_Brazil_340.pickle │ │ │ │ ├── y_Brazil_35.pickle │ │ │ │ ├── y_Brazil_350.pickle │ │ │ │ ├── y_Brazil_360.pickle │ │ │ │ ├── y_Brazil_370.pickle │ │ │ │ ├── y_Brazil_38.pickle │ │ │ │ ├── y_Brazil_380.pickle │ │ │ │ ├── y_Brazil_390.pickle │ │ │ │ ├── y_Brazil_400.pickle │ │ │ │ ├── y_Brazil_410.pickle │ │ │ │ ├── y_Brazil_420.pickle │ │ │ │ ├── y_Brazil_430.pickle │ │ │ │ ├── y_Brazil_440.pickle │ │ │ │ ├── y_Brazil_45.pickle │ │ │ │ ├── y_Brazil_450.pickle │ │ │ │ ├── y_Brazil_460.pickle │ │ │ │ ├── y_Brazil_470.pickle │ │ │ │ ├── y_Brazil_480.pickle │ │ │ │ ├── y_Brazil_490.pickle │ │ │ │ ├── y_Brazil_55.pickle │ │ │ │ ├── y_Brazil_60.pickle │ │ │ │ ├── y_Brazil_65.pickle │ │ │ │ ├── y_Brazil_70.pickle │ │ │ │ ├── y_Brazil_75.pickle │ │ │ │ ├── y_Brazil_80.pickle │ │ │ │ ├── y_Brazil_85.pickle │ │ │ │ └── y_Brazil_95.pickle │ │ ├── Chile_26Oct.csv │ │ ├── Chile_wdates23Sept.csv │ │ ├── NSW_SUA_SA2_LGA24Oct.pkl │ │ ├── USA14Oct.csv │ │ ├── USA_Cases_Zipf.png │ │ ├── USA_Pop_Zipf.png │ │ ├── covid19_NSW.csv │ │ ├── covid19_USA.csv │ │ ├── covid19_brazil.csv │ │ ├── covid19_chile.csv │ │ ├── dataframe_empty_USA.pikle │ │ ├── dataframe_empty_brazil.pikle │ │ ├── list_delays_Brazil.pikle │ │ ├── postcodeCases24Oct.csv │ │ ├── postcodeCaseswDates24Oct.csv │ │ ├── results_covid19_NSW.pickle │ │ ├── results_covid19_USA.pickle │ │ ├── results_covid19_brazil.pickle │ │ ├── results_covid19_chile.pickle │ │ ├── x_covid19_NSW.pickle │ │ ├── x_covid19_USA.pickle │ │ ├── x_covid19_brazil.pickle │ │ ├── x_covid19_chile.pickle │ │ ├── y_covid19_NSW.pickle │ │ ├── y_covid19_USA.pickle │ │ ├── y_covid19_brazil.pickle │ │ └── y_covid19_chile.pickle │ └── raw_data │ │ ├── .DS_Store │ │ ├── backup │ │ ├── covid19_NSW.txt │ │ ├── covid19_USA.txt │ │ ├── covid19_brazil.txt │ │ └── covid19_chile.txt │ │ ├── covid19_NSW.txt │ │ ├── covid19_USA.txt │ │ ├── covid19_brazil.txt │ │ └── covid19_chile.txt ├── eurostat │ ├── #EUROSTAT_culture1_pop_2011# │ ├── .#EUROSTAT_culture1_pop_2011 │ ├── EUROSTAT_culture1_pop_2011 │ ├── EUROSTAT_culture2_pop_2011 │ ├── EUROSTAT_culture3_pop_2011 │ ├── EUROSTAT_culture4_pop_2011 │ ├── EUROSTAT_culture5_pop_2011 │ ├── EUROSTAT_pop_culture_01.py │ ├── Readme │ ├── __init__.py │ ├── __init__.py~ │ ├── __pycache__ │ │ ├── __init__.cpython-35.pyc │ │ ├── __init__.cpython-36.pyc │ │ └── __init__.cpython-38.pyc │ ├── eu_1977_2012_total_patent.csv │ ├── eu_1990_2023_landarea.csv │ ├── eu_1990_2023_population.csv │ ├── eu_1990_2023_totalarea.csv │ ├── eu_1995_2021_gva_euro_millions.csv │ ├── eu_1996_2016_trademarks_permillion.csv │ ├── eu_2000_2021_gdp_euro_millions_currentprices.csv │ ├── eu_2000_2021_gdp_euro_millions_purchasingpower.csv │ ├── eu_2000_2021_gdp_euro_perperson_currentprices.csv │ ├── eu_2000_2021_gdp_euro_perperson_purchasingpower.csv │ ├── eu_2008_2020_burglaries.csv │ ├── eu_2008_2020_homicides.csv │ ├── eu_2008_2020_motortheft.csv │ ├── eu_2008_2020_robberies.csv │ ├── eu_2009_2022_lowersecondary.csv │ ├── eu_2009_2022_tertiary.csv │ ├── eu_2009_2022_uppersecondary_to_nontertiary.csv │ ├── eu_2009_2022_uppersecondary_to_tertiary.csv │ ├── eurostat.py │ ├── eurostat_formatting.ipynb │ └── raw_data │ │ ├── urb_cecfi-1 │ │ ├── urb_cecfi_1_Data.csv │ │ └── urb_cecfi_Label.csv │ │ ├── urb_cpop1 │ │ ├── urb_cpop1_1_Data.csv │ │ └── urb_cpop1_Label.csv │ │ └── urb_ctour │ │ ├── urb_ctour_1_Data.csv │ │ └── urb_ctour_Label.csv ├── germany │ ├── GERcity_gdp_pop_2012 │ ├── GERcounty_gdp_pop_2012 │ ├── README │ ├── __init__.py │ └── raw_data │ │ ├── ger_cities_gdp_1992_2012.csv │ │ └── ger_cities_gdp_per_capita_1992_2012.csv ├── new_dataset │ ├── __init__.py │ ├── __init__.py~ │ ├── __pycache__ │ │ ├── __init__.cpython-35.pyc │ │ ├── __init__.cpython-36.pyc │ │ └── __init__.cpython-38.pyc │ └── generic_dataset.txt ├── new_dataset2 │ ├── __init__.py │ ├── __init__.py~ │ ├── __pycache__ │ │ ├── __init__.cpython-35.pyc │ │ ├── __init__.cpython-36.pyc │ │ └── __init__.cpython-38.pyc │ ├── generic_dataset.txt │ └── generic_dataset.txt~ ├── oecd │ ├── OECD_gdp_pop_2010 │ ├── OECD_patents_pop_2008 │ ├── OECS_pop_gdp_01.py │ ├── OECS_pop_patents_01.py │ ├── Readme │ ├── __init__.py │ ├── __init__.py~ │ ├── __pycache__ │ │ ├── __init__.cpython-35.pyc │ │ ├── __init__.cpython-36.pyc │ │ └── __init__.cpython-38.pyc │ └── raw_data │ │ ├── CITIES_gdp_raw.csv │ │ ├── CITIES_patents_raw.csv │ │ └── CITIES_population_raw.csv ├── uk │ ├── Readme │ ├── __init__.py │ ├── __init__.py~ │ ├── __pycache__ │ │ ├── __init__.cpython-35.pyc │ │ ├── __init__.cpython-36.pyc │ │ └── __init__.cpython-38.pyc │ └── raw_data │ │ ├── SumsP0D14F30.txt │ │ └── SumsP50D14F30.txt └── usa │ ├── README │ ├── Readme.md │ ├── USA-locations.csv │ ├── USmetro_gdp_pop_2013 │ ├── USmetro_pop_gdp_01.py │ ├── __init__.py │ ├── __init__.py~ │ ├── __pycache__ │ ├── __init__.cpython-35.pyc │ ├── __init__.cpython-36.pyc │ └── __init__.cpython-38.pyc │ ├── america_formatting.ipynb │ ├── metropolitan-miles.csv │ ├── miles-location.csv │ ├── raw_data │ ├── US_metro_gdp_2010.csv │ ├── US_metro_gdp_2011.csv │ ├── US_metro_gdp_2012.csv │ ├── US_metro_gdp_2013.csv │ ├── US_metro_pop_2013.csv │ ├── US_metro_pop_2013.xls │ └── hm71.xls │ ├── us_2010_2022_mean_inc_tot.csv │ ├── us_2010_2022_med_inc_tot.csv │ ├── us_2010_2022_population.csv │ ├── us_2010_2022_pov_tot.csv │ ├── us_2010_2022_trav_time.csv │ ├── us_2015_2022_hs_tot.csv │ └── us_area.csv ├── notebooks ├── Notebook-AreaPopModels.ipynb ├── Notebook-FittingModels-Colab.ipynb ├── Notebook-FittingModels.ipynb ├── Notebook-SpatialModels-Colab.ipynb ├── Notebook-SpatialModels.ipynb ├── Notebook-covid19-Colab.ipynb ├── Notebook-covid19_results.ipynb ├── __pycache__ │ ├── analysis.cpython-35.pyc │ ├── analysis.cpython-36.pyc │ ├── best_parameters.cpython-35.pyc │ ├── best_parameters.cpython-36.pyc │ ├── pvalue_population.cpython-35.pyc │ └── pvalue_population.cpython-36.pyc └── _results │ ├── .DS_Store │ ├── mle_ConstrainedDAnalysis_covid19_brazil_2_100.json │ ├── mle_ConstrainedDAnalysis_eurostat_cinema_attendance_512_100.json │ ├── mle_ConstrainedDAnalysis_eurostat_cinema_seats_512_100.json │ ├── mle_ConstrainedDAnalysis_eurostat_libraries_512_100.json │ ├── mle_ConstrainedDAnalysis_eurostat_museum_visitors_512_100.json │ ├── mle_ConstrainedDAnalysis_eurostat_theaters_512_100.json │ ├── mle_ConstrainedDAnalysis_ocde_gdp_512_100.json │ ├── mle_ConstrainedDAnalysis_ocde_patents_512_100.json │ ├── mle_ConstrainedDAnalysis_uk_income_16_100.json │ ├── mle_ConstrainedDAnalysis_uk_income_1_100.json │ ├── mle_ConstrainedDAnalysis_uk_income_512_100.json │ ├── mle_ConstrainedDAnalysis_uk_patents_512_100.json │ ├── mle_ConstrainedDAnalysis_uk_train_512_100.json │ ├── mle_ConstrainedDAnalysis_usa_gdp_1_100.json │ ├── mle_ConstrainedDAnalysis_usa_gdp_2_100.json │ ├── mle_ConstrainedDAnalysis_usa_gdp_512_100.json │ ├── mle_ConstrainedDAnalysis_usa_miles_512_100.json │ ├── mle_ConstrainedDAnalysis_usa_miles_8_100.json │ ├── mle_ConstrainedDFixedBetaAnalysis_covid19_brazil_2_100.json │ ├── mle_ConstrainedDFixedBetaAnalysis_eurostat_cinema_attendance_512_100.json │ ├── mle_ConstrainedDFixedBetaAnalysis_eurostat_cinema_seats_512_100.json │ ├── mle_ConstrainedDFixedBetaAnalysis_eurostat_libraries_512_100.json │ ├── mle_ConstrainedDFixedBetaAnalysis_eurostat_museum_visitors_512_100.json │ ├── mle_ConstrainedDFixedBetaAnalysis_eurostat_theaters_512_100.json │ ├── mle_ConstrainedDFixedBetaAnalysis_ocde_gdp_512_100.json │ ├── mle_ConstrainedDFixedBetaAnalysis_ocde_patents_512_100.json │ ├── mle_ConstrainedDFixedBetaAnalysis_uk_income_16_100.json │ ├── mle_ConstrainedDFixedBetaAnalysis_uk_income_1_100.json │ ├── mle_ConstrainedDFixedBetaAnalysis_uk_income_512_100.json │ ├── mle_ConstrainedDFixedBetaAnalysis_uk_patents_512_100.json │ ├── mle_ConstrainedDFixedBetaAnalysis_uk_train_512_100.json │ ├── mle_ConstrainedDFixedBetaAnalysis_usa_gdp_1_100.json │ ├── mle_ConstrainedDFixedBetaAnalysis_usa_gdp_2_100.json │ ├── mle_ConstrainedDFixedBetaAnalysis_usa_gdp_512_100.json │ ├── mle_ConstrainedDFixedBetaAnalysis_usa_miles_512_100.json │ ├── mle_ConstrainedDFixedBetaAnalysis_usa_miles_8_100.json │ ├── mle_FixedDAnalysis_eurostat_cinema_attendance_512_100.json │ ├── mle_FixedDAnalysis_eurostat_cinema_seats_512_100.json │ ├── mle_FixedDAnalysis_eurostat_libraries_512_100.json │ ├── mle_FixedDAnalysis_eurostat_museum_visitors_512_100.json │ ├── mle_FixedDAnalysis_eurostat_theaters_512_100.json │ ├── mle_FixedDAnalysis_ocde_gdp_512_100.json │ ├── mle_FixedDAnalysis_ocde_patents_512_100.json │ ├── mle_FixedDAnalysis_uk_income_512_100.json │ ├── mle_FixedDAnalysis_uk_patents_512_100.json │ ├── mle_FixedDAnalysis_uk_train_512_100.json │ ├── mle_FixedDAnalysis_usa_gdp_512_100.json │ ├── mle_FixedDAnalysis_usa_miles_512_100.json │ ├── mle_FixedDFixedBetaAnalysis_eurostat_cinema_attendance_512_100.json │ ├── mle_FixedDFixedBetaAnalysis_eurostat_cinema_seats_512_100.json │ ├── mle_FixedDFixedBetaAnalysis_eurostat_libraries_512_100.json │ ├── mle_FixedDFixedBetaAnalysis_eurostat_museum_visitors_512_100.json │ ├── mle_FixedDFixedBetaAnalysis_eurostat_theaters_512_100.json │ ├── mle_FixedDFixedBetaAnalysis_ocde_gdp_512_100.json │ ├── mle_FixedDFixedBetaAnalysis_ocde_patents_512_100.json │ ├── mle_FixedDFixedBetaAnalysis_uk_income_512_100.json │ ├── mle_FixedDFixedBetaAnalysis_uk_patents_512_100.json │ ├── mle_FixedDFixedBetaAnalysis_uk_train_512_100.json │ ├── mle_FixedDFixedBetaAnalysis_usa_gdp_512_100.json │ ├── mle_FixedDFixedBetaAnalysis_usa_miles_512_100.json │ ├── mle_LogNormalAnalysis_covid19_brazil_2_100.json │ ├── mle_LogNormalAnalysis_eurostat_cinema_attendance_512_100.json │ ├── mle_LogNormalAnalysis_eurostat_cinema_seats_512_100.json │ ├── mle_LogNormalAnalysis_eurostat_libraries_512_100.json │ ├── mle_LogNormalAnalysis_eurostat_museum_visitors_512_100.json │ ├── mle_LogNormalAnalysis_eurostat_theaters_512_100.json │ ├── mle_LogNormalAnalysis_ocde_gdp_512_100.json │ ├── mle_LogNormalAnalysis_ocde_patents_512_100.json │ ├── mle_LogNormalAnalysis_uk_income_15_100.json │ ├── mle_LogNormalAnalysis_uk_income_16_100.json │ ├── mle_LogNormalAnalysis_uk_income_1_100.json │ ├── mle_LogNormalAnalysis_uk_income_512_100.json │ ├── mle_LogNormalAnalysis_uk_patents_512_100.json │ ├── mle_LogNormalAnalysis_uk_train_512_100.json │ ├── mle_LogNormalAnalysis_usa_gdp_1_100.json │ ├── mle_LogNormalAnalysis_usa_gdp_2_100.json │ ├── mle_LogNormalAnalysis_usa_gdp_512_100.json │ ├── mle_LogNormalAnalysis_usa_miles_512_100.json │ ├── mle_LogNormalAnalysis_usa_miles_8_100.json │ ├── mle_LogNormalFixedBetaAnalysis_covid19_brazil_2_100.json │ ├── mle_LogNormalFixedBetaAnalysis_eurostat_cinema_attendance_512_100.json │ ├── mle_LogNormalFixedBetaAnalysis_eurostat_cinema_seats_512_100.json │ ├── mle_LogNormalFixedBetaAnalysis_eurostat_libraries_512_100.json │ ├── mle_LogNormalFixedBetaAnalysis_eurostat_museum_visitors_512_100.json │ ├── mle_LogNormalFixedBetaAnalysis_eurostat_theaters_512_100.json │ ├── mle_LogNormalFixedBetaAnalysis_ocde_gdp_512_100.json │ ├── mle_LogNormalFixedBetaAnalysis_ocde_patents_512_100.json │ ├── mle_LogNormalFixedBetaAnalysis_uk_income_16_100.json │ ├── mle_LogNormalFixedBetaAnalysis_uk_income_1_100.json │ ├── mle_LogNormalFixedBetaAnalysis_uk_income_512_100.json │ ├── mle_LogNormalFixedBetaAnalysis_uk_patents_512_100.json │ ├── mle_LogNormalFixedBetaAnalysis_uk_train_512_100.json │ ├── mle_LogNormalFixedBetaAnalysis_usa_gdp_1_100.json │ ├── mle_LogNormalFixedBetaAnalysis_usa_gdp_2_100.json │ ├── mle_LogNormalFixedBetaAnalysis_usa_gdp_512_100.json │ ├── mle_LogNormalFixedBetaAnalysis_usa_miles_512_100.json │ ├── mle_LogNormalFixedBetaAnalysis_usa_miles_8_100.json │ ├── mle_LogNormalFixedDAnalysis_covid19_brazil_2_100.json │ ├── mle_LogNormalFixedDAnalysis_eurostat_cinema_attendance_512_100.json │ ├── mle_LogNormalFixedDAnalysis_eurostat_cinema_seats_512_100.json │ ├── mle_LogNormalFixedDAnalysis_eurostat_libraries_512_100.json │ ├── mle_LogNormalFixedDAnalysis_eurostat_museum_visitors_512_100.json │ ├── mle_LogNormalFixedDAnalysis_eurostat_theaters_512_100.json │ ├── mle_LogNormalFixedDAnalysis_ocde_gdp_512_100.json │ ├── mle_LogNormalFixedDAnalysis_ocde_patents_512_100.json │ ├── mle_LogNormalFixedDAnalysis_uk_income_1_100.json │ ├── mle_LogNormalFixedDAnalysis_uk_income_512_100.json │ ├── mle_LogNormalFixedDAnalysis_uk_patents_512_100.json │ ├── mle_LogNormalFixedDAnalysis_uk_train_512_100.json │ ├── mle_LogNormalFixedDAnalysis_usa_gdp_1_100.json │ ├── mle_LogNormalFixedDAnalysis_usa_gdp_2_100.json │ ├── mle_LogNormalFixedDAnalysis_usa_gdp_512_100.json │ ├── mle_LogNormalFixedDAnalysis_usa_miles_512_100.json │ ├── mle_LogNormalFixedDAnalysis_usa_miles_8_100.json │ ├── mle_LogNormalFixedDFixedB_eurostat_cinema_attendance_512_100.json │ ├── mle_LogNormalFixedDFixedB_eurostat_cinema_seats_512_100.json │ ├── mle_LogNormalFixedDFixedB_eurostat_libraries_512_100.json │ ├── mle_LogNormalFixedDFixedB_eurostat_museum_visitors_512_100.json │ ├── mle_LogNormalFixedDFixedB_eurostat_theaters_512_100.json │ ├── mle_LogNormalFixedDFixedB_ocde_gdp_512_100.json │ ├── mle_LogNormalFixedDFixedB_ocde_patents_512_100.json │ ├── mle_LogNormalFixedDFixedB_uk_income_512_100.json │ ├── mle_LogNormalFixedDFixedB_uk_patents_512_100.json │ ├── mle_LogNormalFixedDFixedB_uk_train_512_100.json │ ├── mle_LogNormalFixedDFixedB_usa_gdp_512_100.json │ ├── mle_LogNormalFixedDFixedB_usa_miles_512_100.json │ ├── mle_LogNormalFixedDFixedBetaAnalysis_eurostat_cinema_attendance_512_100.json │ ├── mle_LogNormalFixedDFixedBetaAnalysis_eurostat_cinema_seats_512_100.json │ ├── mle_LogNormalFixedDFixedBetaAnalysis_eurostat_libraries_512_100.json │ ├── mle_LogNormalFixedDFixedBetaAnalysis_eurostat_museum_visitors_512_100.json │ ├── mle_LogNormalFixedDFixedBetaAnalysis_eurostat_theaters_512_100.json │ ├── mle_LogNormalFixedDFixedBetaAnalysis_ocde_gdp_512_100.json │ ├── mle_LogNormalFixedDFixedBetaAnalysis_ocde_patents_512_100.json │ ├── mle_LogNormalFixedDFixedBetaAnalysis_uk_income_512_100.json │ ├── mle_LogNormalFixedDFixedBetaAnalysis_uk_patents_512_100.json │ ├── mle_LogNormalFixedDFixedBetaAnalysis_uk_train_512_100.json │ ├── mle_LogNormalFixedDFixedBetaAnalysis_usa_gdp_512_100.json │ ├── mle_LogNormalFixedDFixedBetaAnalysis_usa_miles_512_100.json │ ├── mle_LogNormalFixedD_eurostat_cinema_attendance_512_100.json │ ├── mle_LogNormalFixedD_eurostat_cinema_seats_512_100.json │ ├── mle_LogNormalFixedD_eurostat_libraries_512_100.json │ ├── mle_LogNormalFixedD_eurostat_museum_visitors_512_100.json │ ├── mle_LogNormalFixedD_eurostat_theaters_512_100.json │ ├── mle_LogNormalFixedD_ocde_gdp_512_100.json │ ├── mle_LogNormalFixedD_ocde_patents_512_100.json │ ├── mle_LogNormalFixedD_uk_income_512_100.json │ ├── mle_LogNormalFixedD_uk_patents_512_100.json │ ├── mle_LogNormalFixedD_uk_train_512_100.json │ ├── mle_LogNormalFixedD_usa_gdp_512_100.json │ ├── mle_LogNormalFixedD_usa_miles_512_100.json │ ├── mle_LogNormalFreeDFixedB_eurostat_cinema_attendance_512_100.json │ ├── mle_LogNormalFreeDFixedB_eurostat_cinema_seats_512_100.json │ ├── mle_LogNormalFreeDFixedB_eurostat_libraries_512_100.json │ ├── mle_LogNormalFreeDFixedB_eurostat_museum_visitors_512_100.json │ ├── mle_LogNormalFreeDFixedB_eurostat_theaters_512_100.json │ ├── mle_LogNormalFreeDFixedB_ocde_gdp_512_100.json │ ├── mle_LogNormalFreeDFixedB_ocde_patents_512_100.json │ ├── mle_LogNormalFreeDFixedB_uk_income_512_100.json │ ├── mle_LogNormalFreeDFixedB_uk_patents_512_100.json │ ├── mle_LogNormalFreeDFixedB_uk_train_512_100.json │ ├── mle_LogNormalFreeDFixedB_usa_gdp_512_100.json │ ├── mle_LogNormalFreeDFixedB_usa_miles_512_100.json │ ├── mle_LogNormalFreeD_eurostat_cinema_attendance_512_100.json │ ├── mle_LogNormalFreeD_eurostat_cinema_seats_512_100.json │ ├── mle_LogNormalFreeD_eurostat_libraries_512_100.json │ ├── mle_LogNormalFreeD_eurostat_museum_visitors_512_100.json │ ├── mle_LogNormalFreeD_eurostat_theaters_512_100.json │ ├── mle_LogNormalFreeD_ocde_gdp_512_100.json │ ├── mle_LogNormalFreeD_ocde_patents_512_100.json │ ├── mle_LogNormalFreeD_uk_income_512_100.json │ ├── mle_LogNormalFreeD_uk_patents_512_100.json │ ├── mle_LogNormalFreeD_uk_train_512_100.json │ ├── mle_LogNormalFreeD_usa_gdp_512_100.json │ ├── mle_LogNormalFreeD_usa_miles_512_100.json │ ├── mle_NormalFixedD_ocde_gdp_512_100.json │ ├── mle_NormalFreeDFixedB_eurostat_cinema_attendance_512_100.json │ ├── mle_NormalFreeDFixedB_eurostat_cinema_seats_512_100.json │ ├── mle_NormalFreeDFixedB_eurostat_libraries_512_100.json │ ├── mle_NormalFreeDFixedB_eurostat_museum_visitors_512_100.json │ ├── mle_NormalFreeDFixedB_eurostat_theaters_512_100.json │ ├── mle_NormalFreeDFixedB_ocde_gdp_512_100.json │ ├── mle_NormalFreeDFixedB_ocde_patents_512_100.json │ ├── mle_NormalFreeDFixedB_uk_income_512_100.json │ ├── mle_NormalFreeDFixedB_uk_patents_512_100.json │ ├── mle_NormalFreeDFixedB_uk_train_512_100.json │ ├── mle_NormalFreeDFixedB_usa_gdp_512_100.json │ ├── mle_NormalFreeDFixedB_usa_miles_512_100.json │ ├── mle_NormalFreeD_eurostat_cinema_attendance_512_100.json │ ├── mle_NormalFreeD_eurostat_cinema_seats_512_100.json │ ├── mle_NormalFreeD_eurostat_libraries_512_100.json │ ├── mle_NormalFreeD_eurostat_museum_visitors_512_100.json │ ├── mle_NormalFreeD_eurostat_theaters_512_100.json │ ├── mle_NormalFreeD_ocde_gdp_512_100.json │ ├── mle_NormalFreeD_ocde_patents_512_100.json │ ├── mle_NormalFreeD_uk_income_512_100.json │ ├── mle_NormalFreeD_uk_patents_512_100.json │ ├── mle_NormalFreeD_uk_train_512_100.json │ ├── mle_NormalFreeD_usa_gdp_512_100.json │ ├── mle_NormalFreeD_usa_miles_512_100.json │ ├── mle_PopulationAnalysis_covid19_brazil_2_100.json │ ├── mle_PopulationAnalysis_eurostat_cinema_attendance_512_100.json │ ├── mle_PopulationAnalysis_eurostat_cinema_seats_512_100.json │ ├── mle_PopulationAnalysis_eurostat_libraries_512_100.json │ ├── mle_PopulationAnalysis_eurostat_museum_visitors_512_100.json │ ├── mle_PopulationAnalysis_eurostat_theaters_512_100.json │ ├── mle_PopulationAnalysis_ocde_gdp_512_100.json │ ├── mle_PopulationAnalysis_ocde_patents_512_100.json │ ├── mle_PopulationAnalysis_uk_income_16_100.json │ ├── mle_PopulationAnalysis_uk_income_1_100.json │ ├── mle_PopulationAnalysis_uk_income_512_100.json │ ├── mle_PopulationAnalysis_uk_patents_512_100.json │ ├── mle_PopulationAnalysis_uk_train_512_100.json │ ├── mle_PopulationAnalysis_usa_gdp_1_100.json │ ├── mle_PopulationAnalysis_usa_gdp_2_100.json │ ├── mle_PopulationAnalysis_usa_gdp_512_100.json │ ├── mle_PopulationAnalysis_usa_miles_512_100.json │ ├── mle_PopulationAnalysis_usa_miles_8_100.json │ ├── mle_PopulationFixedGammaAnalysis_covid19_brazil_2_100.json │ ├── mle_PopulationFixedGammaAnalysis_eurostat_cinema_attendance_512_100.json │ ├── mle_PopulationFixedGammaAnalysis_eurostat_cinema_seats_512_100.json │ ├── mle_PopulationFixedGammaAnalysis_eurostat_libraries_512_100.json │ ├── mle_PopulationFixedGammaAnalysis_eurostat_museum_visitors_512_100.json │ ├── mle_PopulationFixedGammaAnalysis_eurostat_theaters_512_100.json │ ├── mle_PopulationFixedGammaAnalysis_ocde_gdp_512_100.json │ ├── mle_PopulationFixedGammaAnalysis_ocde_patents_512_100.json │ ├── mle_PopulationFixedGammaAnalysis_uk_income_16_100.json │ ├── mle_PopulationFixedGammaAnalysis_uk_income_1_100.json │ ├── mle_PopulationFixedGammaAnalysis_uk_income_512_100.json │ ├── mle_PopulationFixedGammaAnalysis_uk_patents_512_100.json │ ├── mle_PopulationFixedGammaAnalysis_uk_train_512_100.json │ ├── mle_PopulationFixedGammaAnalysis_usa_gdp_1_100.json │ ├── mle_PopulationFixedGammaAnalysis_usa_gdp_2_100.json │ ├── mle_PopulationFixedGammaAnalysis_usa_gdp_512_100.json │ ├── mle_PopulationFixedGammaAnalysis_usa_miles_512_100.json │ ├── mle_PopulationFixedGammaAnalysis_usa_miles_8_100.json │ ├── mle_Population_eurostat_museum_visitors_512_100.json │ ├── pvalue_PopulationAnalysis_covid19_brazil_2_100.json │ ├── pvalue_PopulationAnalysis_eurostat_cinema_attendance_512_100.json │ ├── pvalue_PopulationAnalysis_eurostat_cinema_seats_512_100.json │ ├── pvalue_PopulationAnalysis_eurostat_libraries_512_100.json │ ├── pvalue_PopulationAnalysis_eurostat_museum_visitors_512_100.json │ ├── pvalue_PopulationAnalysis_eurostat_theaters_512_100.json │ ├── pvalue_PopulationAnalysis_ocde_gdp_512_100.json │ ├── pvalue_PopulationAnalysis_ocde_patents_512_100.json │ ├── pvalue_PopulationAnalysis_uk_income_16_100.json │ ├── pvalue_PopulationAnalysis_uk_income_1_100.json │ ├── pvalue_PopulationAnalysis_uk_income_512_100.json │ ├── pvalue_PopulationAnalysis_uk_patents_512_100.json │ ├── pvalue_PopulationAnalysis_uk_train_512_100.json │ ├── pvalue_PopulationAnalysis_usa_gdp_1_100.json │ ├── pvalue_PopulationAnalysis_usa_gdp_2_100.json │ ├── pvalue_PopulationAnalysis_usa_gdp_512_100.json │ ├── pvalue_PopulationAnalysis_usa_miles_512_100.json │ ├── pvalue_PopulationAnalysis_usa_miles_8_100.json │ ├── pvalue_PopulationFixedGammaAnalysis_covid19_brazil_2_100.json │ ├── pvalue_PopulationFixedGammaAnalysis_eurostat_cinema_attendance_512_100.json │ ├── pvalue_PopulationFixedGammaAnalysis_eurostat_cinema_seats_512_100.json │ ├── pvalue_PopulationFixedGammaAnalysis_eurostat_libraries_512_100.json │ ├── pvalue_PopulationFixedGammaAnalysis_eurostat_museum_visitors_512_100.json │ ├── pvalue_PopulationFixedGammaAnalysis_eurostat_theaters_512_100.json │ ├── pvalue_PopulationFixedGammaAnalysis_ocde_gdp_512_100.json │ ├── pvalue_PopulationFixedGammaAnalysis_ocde_patents_512_100.json │ ├── pvalue_PopulationFixedGammaAnalysis_uk_income_16_100.json │ ├── pvalue_PopulationFixedGammaAnalysis_uk_income_1_100.json │ ├── pvalue_PopulationFixedGammaAnalysis_uk_income_512_100.json │ ├── pvalue_PopulationFixedGammaAnalysis_uk_patents_512_100.json │ ├── pvalue_PopulationFixedGammaAnalysis_uk_train_512_100.json │ ├── pvalue_PopulationFixedGammaAnalysis_usa_gdp_1_100.json │ ├── pvalue_PopulationFixedGammaAnalysis_usa_gdp_2_100.json │ ├── pvalue_PopulationFixedGammaAnalysis_usa_gdp_512_100.json │ ├── pvalue_PopulationFixedGammaAnalysis_usa_miles_512_100.json │ └── pvalue_PopulationFixedGammaAnalysis_usa_miles_8_100.json └── src ├── __pycache__ ├── analysis.cpython-36.pyc ├── analysis.cpython-38.pyc ├── best_parameters.cpython-36.pyc ├── best_parameters.cpython-38.pyc ├── pvalue_population.cpython-36.pyc └── pvalue_population.cpython-38.pyc ├── analysis.py ├── analysis_run.py ├── analyze.py ├── best_parameters.py ├── pvalue_population.py └── spatial.py /AUTHORS.txt: -------------------------------------------------------------------------------- 1 | Eduardo G. Altmann 2 | Jorge C. Leitão 3 | José Miotto 4 | Martin Gerlach 5 | Jimena Espinoza 6 | Isaac Riad 7 | -------------------------------------------------------------------------------- /data/australia/SUA_LatLong.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/australia/SUA_LatLong.xlsx -------------------------------------------------------------------------------- /data/australia/SUA_association_2016_2021.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/australia/SUA_association_2016_2021.xlsx -------------------------------------------------------------------------------- /data/brazil/Readme.me: -------------------------------------------------------------------------------- 1 | This database contains different indexes of all municipalities of Brazil. The default data are from the year 2010 and are provided by Brazil’s Health Ministry (Brazilian Health Ministry. July 2015; population corresponds to census data). 2 | 3 | — GDP: N=5565, gross domestic product. 4 | 5 | — AIDS: N=1812, number of deaths by AIDS. 6 | 7 | — External: N=5286, number of deaths by external causes. 8 | -------------------------------------------------------------------------------- /data/brazil/__pycache__/__init__.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/brazil/__pycache__/__init__.cpython-36.pyc -------------------------------------------------------------------------------- /data/brazil/__pycache__/__init__.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/brazil/__pycache__/__init__.cpython-38.pyc -------------------------------------------------------------------------------- /data/brazil/__pycache__/data.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/brazil/__pycache__/data.cpython-36.pyc -------------------------------------------------------------------------------- /data/brazil/__pycache__/data.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/brazil/__pycache__/data.cpython-38.pyc -------------------------------------------------------------------------------- /data/brazil/raw_data/aids-1996-2012.txt: -------------------------------------------------------------------------------- 1 | data collected from: 2 | http://www2.aids.gov.br/cgi/deftohtm.exe?sim/obtbr.def 3 | -------------------------------------------------------------------------------- /data/brazil/raw_data/externalCauses-1996-2012.txt: -------------------------------------------------------------------------------- 1 | Data obtained from: tabnet.datasus.gov.br/cgi/deftohtm.exe?sim/cnv/ext10br.def 2 | 3 | It corresponds to deaths by external causes in Municipalities of Brazil in the year 2010 4 | 5 | The original source is MS/SVS/CGIAE - Sistema de Informações sobre Mortalidade - SIM 6 | -------------------------------------------------------------------------------- /data/brazil/raw_data/gdp-2000-2012.txt: -------------------------------------------------------------------------------- 1 | data collected from: 2 | http://tabnet.datasus.gov.br/cgi/deftohtm.exe?ibge/cnv/pibmunbr.def 3 | 4 | Source: IBGE, em parceria com os Órgãos Estaduais de Estatística, Secretarias Estaduais de Governo e Superintendência da Zona Franca de Manaus - SUFRAMA. 5 | -------------------------------------------------------------------------------- /data/brazil/raw_data/population-1996-2012.txt: -------------------------------------------------------------------------------- 1 | data collected from: 2 | http://tabnet.datasus.gov.br/cgi/tabcgi.exe?ibge/cnv/popbr.def 3 | 4 | Sources: 5 | 6 | 1980, 1991, 2000 e 2010: IBGE - Censos Demográficos 7 | 1996: IBGE - Contagem Populacional 8 | 1981-1990, 1992-1999, 2001-2006: IBGE - Estimativas preliminares para os anos intercensitários dos totais populacionais, estratificadas por idade e sexo pelo MS/SGEP/Datasus. 9 | 2007-2009: IBGE - Estimativas elaboradas no âmbito do Projeto UNFPA/IBGE (BRA/4/P31A) - População e Desenvolvimento. Coordenação de População e Indicadores Sociais. 10 | 2011-2012: IBGE - Estimativas populacionais enviadas para o TCU, estratificadas por idade e sexo pelo MS/SGEP/Datasus. 11 | 12 | -------------------------------------------------------------------------------- /data/covid19/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/.DS_Store -------------------------------------------------------------------------------- /data/covid19/__pycache__/__init__.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/__pycache__/__init__.cpython-38.pyc -------------------------------------------------------------------------------- /data/covid19/_generated_files/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/.DS_Store -------------------------------------------------------------------------------- /data/covid19/_generated_files/AllScales24Oct.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/AllScales24Oct.pkl -------------------------------------------------------------------------------- /data/covid19/_generated_files/All_Pop_Zipf.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/All_Pop_Zipf.png -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/.DS_Store -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/.DS_Store -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/Betas_Brazil.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/Betas_Brazil.png -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_105.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_105.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_115.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_115.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_125.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_125.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_135.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_135.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_145.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_145.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_155.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_155.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_165.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_165.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_175.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_175.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_185.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_185.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_195.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_195.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_205.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_205.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_215.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_215.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_225.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_225.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_235.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_235.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_245.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_245.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_25.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_25.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_255.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_255.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_265.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_265.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_275.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_275.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_285.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_285.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_295.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_295.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_30.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_30.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_300.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_300.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_310.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_310.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_320.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_320.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_330.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_330.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_340.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_340.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_35.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_35.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_350.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_350.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_360.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_360.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_370.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_370.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_38.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_38.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_380.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_380.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_390.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_390.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_400.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_400.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_410.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_410.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_420.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_420.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_430.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_430.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_440.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_440.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_45.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_45.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_450.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_450.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_460.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_460.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_470.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_470.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_480.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_480.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_490.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_490.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_55.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_55.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_60.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_60.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_65.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_65.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_70.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_70.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_75.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_75.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_80.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_80.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_85.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_85.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_95.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/results_Brazil_95.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_105.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_105.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_115.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_115.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_125.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_125.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_135.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_135.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_145.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_145.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_155.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_155.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_165.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_165.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_175.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_175.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_185.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_185.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_195.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_195.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_205.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_205.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_215.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_215.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_225.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_225.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_235.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_235.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_245.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_245.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_25.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_25.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_255.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_255.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_265.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_265.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_275.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_275.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_285.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_285.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_295.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_295.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_30.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_30.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_300.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_300.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_310.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_310.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_320.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_320.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_330.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_330.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_340.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_340.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_35.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_35.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_350.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_350.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_360.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_360.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_370.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_370.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_380.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_380.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_38pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_38pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_390.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_390.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_400.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_400.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_410.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_410.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_420.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_420.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_430.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_430.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_440.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_440.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_45.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_45.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_450.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_450.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_460.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_460.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_470.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_470.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_480.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_480.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_490.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_490.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_55.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_55.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_60.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_60.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_65.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_65.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_70.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_70.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_75.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_75.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_80.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_80.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_85.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_85.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_95.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/x_Brazil_95.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_105.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_105.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_115.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_115.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_125.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_125.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_135.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_135.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_145.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_145.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_155.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_155.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_165.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_165.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_175.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_175.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_185.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_185.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_195.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_195.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_205.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_205.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_215.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_215.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_225.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_225.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_235.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_235.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_245.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_245.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_25.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_25.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_255.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_255.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_265.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_265.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_275.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_275.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_285.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_285.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_295.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_295.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_30.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_30.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_300.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_300.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_310.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_310.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_320.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_320.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_330.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_330.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_340.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_340.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_35.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_35.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_350.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_350.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_360.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_360.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_370.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_370.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_38.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_38.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_380.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_380.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_390.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_390.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_400.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_400.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_410.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_410.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_420.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_420.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_430.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_430.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_440.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_440.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_45.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_45.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_450.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_450.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_460.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_460.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_470.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_470.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_480.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_480.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_490.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_490.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_55.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_55.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_60.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_60.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_65.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_65.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_70.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_70.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_75.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_75.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_80.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_80.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_85.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_85.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_95.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/Brazil_by_dates/_results/y_Brazil_95.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/NSW_SUA_SA2_LGA24Oct.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/NSW_SUA_SA2_LGA24Oct.pkl -------------------------------------------------------------------------------- /data/covid19/_generated_files/USA_Cases_Zipf.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/USA_Cases_Zipf.png -------------------------------------------------------------------------------- /data/covid19/_generated_files/USA_Pop_Zipf.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/USA_Pop_Zipf.png -------------------------------------------------------------------------------- /data/covid19/_generated_files/dataframe_empty_USA.pikle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/dataframe_empty_USA.pikle -------------------------------------------------------------------------------- /data/covid19/_generated_files/dataframe_empty_brazil.pikle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/dataframe_empty_brazil.pikle -------------------------------------------------------------------------------- /data/covid19/_generated_files/list_delays_Brazil.pikle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/list_delays_Brazil.pikle -------------------------------------------------------------------------------- /data/covid19/_generated_files/results_covid19_NSW.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/results_covid19_NSW.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/results_covid19_USA.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/results_covid19_USA.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/results_covid19_brazil.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/results_covid19_brazil.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/results_covid19_chile.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/results_covid19_chile.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/x_covid19_NSW.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/x_covid19_NSW.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/x_covid19_USA.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/x_covid19_USA.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/x_covid19_brazil.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/x_covid19_brazil.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/x_covid19_chile.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/x_covid19_chile.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/y_covid19_NSW.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/y_covid19_NSW.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/y_covid19_USA.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/y_covid19_USA.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/y_covid19_brazil.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/y_covid19_brazil.pickle -------------------------------------------------------------------------------- /data/covid19/_generated_files/y_covid19_chile.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/_generated_files/y_covid19_chile.pickle -------------------------------------------------------------------------------- /data/covid19/raw_data/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/covid19/raw_data/.DS_Store -------------------------------------------------------------------------------- /data/eurostat/.#EUROSTAT_culture1_pop_2011: -------------------------------------------------------------------------------- 1 | ega@ega-Latitude-E5570.19606:1476935209 -------------------------------------------------------------------------------- /data/eurostat/Readme: -------------------------------------------------------------------------------- 1 | The data is from here: 2 | http://ec.europa.eu/eurostat/web/cities/data/database 3 | 4 | It includes data on european metropolitan areas regarding: 5 | - population 6 | - culture (e.g. number of theaters) 7 | - 'all companies' (is this the number of companies?) 8 | 9 | The tables `EUROSTAT_*` were constructed by merging the different tables. 10 | 11 | New Data (for Area and Population models): 12 | Data sourced from same database (https://ec.europa.eu/eurostat/data/database). It includes data on european metropolitan areas regarding: 13 | - Population from 1990 - 2023 14 | - Land area from 1990 - 2023 15 | - Total area from 1990 - 2023 16 | - EU trade mark applications per million population 1996 - 2016 17 | - EU trade mark applications in total 1977 - 2012 18 | - GDP in million Euros at current market prices 2000 - 2021 19 | - GDP in million Euros purchasing power adjusted 2000 - 2021 20 | - GDP per person in Euros at current market prices 2000 - 2021 21 | - GDP per person in Euros purchasing power adjusted 2000 - 2021 22 | - GVA in million Euros 1995 - 2021 23 | - Burglaries 2008 - 2020 24 | - Homicides 2008 - 2020 25 | - Motortheft 2008 - 2020 26 | - Robberies 2008 - 2020 27 | - Lower secondary education 2009 - 2022 28 | - Upper secondary to nontertiary education 2009 - 2022 29 | - Upper secondary to tertiary education 2009 - 2022 30 | - Teritary education 2009 - 2022 31 | -------------------------------------------------------------------------------- /data/eurostat/__init__.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | 3 | def read_file(file_name): 4 | """ 5 | """ 6 | v = [] 7 | with open(file_name, 'r') as f: 8 | for i, line in enumerate(f): 9 | if i == 0: 10 | continue 11 | v.append(list(map(int, line.strip("\n").split("\t")[1:]))) 12 | v = np.array(v).transpose() 13 | return v[0,:], v[1,:] 14 | 15 | 16 | def cinemaSeats(): 17 | file_name = '../data/eurostat/EUROSTAT_culture1_pop_2011' 18 | return read_file(file_name) 19 | 20 | 21 | def cinemaAttendance(): 22 | file_name = '../data/eurostat/EUROSTAT_culture2_pop_2011' 23 | return read_file(file_name) 24 | 25 | 26 | def museumVisitors(): 27 | file_name = '../data/eurostat/EUROSTAT_culture3_pop_2011' 28 | return read_file(file_name) 29 | 30 | 31 | def theaters(): 32 | file_name = '../data/eurostat/EUROSTAT_culture4_pop_2011' 33 | return read_file(file_name) 34 | 35 | 36 | def libraries(): 37 | file_name = '../data/eurostat/EUROSTAT_culture5_pop_2011' 38 | return read_file(file_name) 39 | -------------------------------------------------------------------------------- /data/eurostat/__init__.py~: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | 3 | def read_file(file_name): 4 | """ 5 | """ 6 | v = [] 7 | with open(file_name, 'r') as f: 8 | for i, line in enumerate(f): 9 | if i == 0: 10 | continue 11 | v.append(list(map(int, line.strip("\n").split("\t")[1:]))) 12 | v = np.array(v).transpose() 13 | return v[0,:], v[1,:] 14 | 15 | 16 | def cinemaSeats(): 17 | file_name = 'eurostat/EUROSTAT_culture1_pop_2011' 18 | return read_file(file_name) 19 | 20 | 21 | def cinemaAttendance(): 22 | file_name = 'eurostat/EUROSTAT_culture2_pop_2011' 23 | return read_file(file_name) 24 | 25 | 26 | def museumVisitors(): 27 | file_name = 'eurostat/EUROSTAT_culture3_pop_2011' 28 | return read_file(file_name) 29 | 30 | 31 | def theaters(): 32 | file_name = 'eurostat/EUROSTAT_culture4_pop_2011' 33 | return read_file(file_name) 34 | 35 | 36 | def libraries(): 37 | file_name = 'eurostat/EUROSTAT_culture5_pop_2011' 38 | return read_file(file_name) 39 | -------------------------------------------------------------------------------- /data/eurostat/__pycache__/__init__.cpython-35.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/__pycache__/__init__.cpython-35.pyc -------------------------------------------------------------------------------- /data/eurostat/__pycache__/__init__.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/__pycache__/__init__.cpython-36.pyc -------------------------------------------------------------------------------- /data/eurostat/__pycache__/__init__.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/__pycache__/__init__.cpython-38.pyc -------------------------------------------------------------------------------- /data/eurostat/eu_1977_2012_total_patent.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/eu_1977_2012_total_patent.csv -------------------------------------------------------------------------------- /data/eurostat/eu_1990_2023_landarea.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/eu_1990_2023_landarea.csv -------------------------------------------------------------------------------- /data/eurostat/eu_1990_2023_population.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/eu_1990_2023_population.csv -------------------------------------------------------------------------------- /data/eurostat/eu_1990_2023_totalarea.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/eu_1990_2023_totalarea.csv -------------------------------------------------------------------------------- /data/eurostat/eu_1995_2021_gva_euro_millions.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/eu_1995_2021_gva_euro_millions.csv -------------------------------------------------------------------------------- /data/eurostat/eu_1996_2016_trademarks_permillion.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/eu_1996_2016_trademarks_permillion.csv -------------------------------------------------------------------------------- /data/eurostat/eu_2000_2021_gdp_euro_millions_currentprices.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/eu_2000_2021_gdp_euro_millions_currentprices.csv -------------------------------------------------------------------------------- /data/eurostat/eu_2000_2021_gdp_euro_millions_purchasingpower.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/eu_2000_2021_gdp_euro_millions_purchasingpower.csv -------------------------------------------------------------------------------- /data/eurostat/eu_2000_2021_gdp_euro_perperson_currentprices.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/eu_2000_2021_gdp_euro_perperson_currentprices.csv -------------------------------------------------------------------------------- /data/eurostat/eu_2000_2021_gdp_euro_perperson_purchasingpower.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/eu_2000_2021_gdp_euro_perperson_purchasingpower.csv -------------------------------------------------------------------------------- /data/eurostat/eu_2008_2020_burglaries.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/eu_2008_2020_burglaries.csv -------------------------------------------------------------------------------- /data/eurostat/eu_2008_2020_homicides.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/eu_2008_2020_homicides.csv -------------------------------------------------------------------------------- /data/eurostat/eu_2008_2020_motortheft.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/eu_2008_2020_motortheft.csv -------------------------------------------------------------------------------- /data/eurostat/eu_2008_2020_robberies.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/eu_2008_2020_robberies.csv -------------------------------------------------------------------------------- /data/eurostat/eu_2009_2022_lowersecondary.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/eu_2009_2022_lowersecondary.csv -------------------------------------------------------------------------------- /data/eurostat/eu_2009_2022_tertiary.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/eu_2009_2022_tertiary.csv -------------------------------------------------------------------------------- /data/eurostat/eu_2009_2022_uppersecondary_to_nontertiary.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/eu_2009_2022_uppersecondary_to_nontertiary.csv -------------------------------------------------------------------------------- /data/eurostat/eu_2009_2022_uppersecondary_to_tertiary.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/eu_2009_2022_uppersecondary_to_tertiary.csv -------------------------------------------------------------------------------- /data/eurostat/eurostat.py: -------------------------------------------------------------------------------- 1 | import os 2 | 3 | file_names = filter(lambda x: 'EUROSTAT' in x, os.listdir('./')) 4 | 5 | def change_encoding(file_names): 6 | for file_name in file_names: 7 | lines = [] 8 | with open('./'+file_name, 'r') as f: 9 | for i, x in enumerate(f): 10 | y = x.rstrip('\n').decode('latin1').encode('utf8') 11 | lines.append(y) 12 | # print x.rstrip('\n').decode('latin1').encode('utf8') 13 | # if i == 10: 14 | # exit() 15 | with open('./'+file_name, 'w') as f: 16 | f.write('\n'.join(lines)) 17 | 18 | change_encoding(file_names) 19 | -------------------------------------------------------------------------------- /data/eurostat/raw_data/urb_cecfi-1/urb_cecfi_1_Data.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/raw_data/urb_cecfi-1/urb_cecfi_1_Data.csv -------------------------------------------------------------------------------- /data/eurostat/raw_data/urb_cecfi-1/urb_cecfi_Label.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/raw_data/urb_cecfi-1/urb_cecfi_Label.csv -------------------------------------------------------------------------------- /data/eurostat/raw_data/urb_cpop1/urb_cpop1_1_Data.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/raw_data/urb_cpop1/urb_cpop1_1_Data.csv -------------------------------------------------------------------------------- /data/eurostat/raw_data/urb_cpop1/urb_cpop1_Label.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/raw_data/urb_cpop1/urb_cpop1_Label.csv -------------------------------------------------------------------------------- /data/eurostat/raw_data/urb_ctour/urb_ctour_1_Data.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/raw_data/urb_ctour/urb_ctour_1_Data.csv -------------------------------------------------------------------------------- /data/eurostat/raw_data/urb_ctour/urb_ctour_Label.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/eurostat/raw_data/urb_ctour/urb_ctour_Label.csv -------------------------------------------------------------------------------- /data/germany/README: -------------------------------------------------------------------------------- 1 | GDP for german cities in 2012 2 | 3 | Data on gdp, and gdp per capita (from which we can infer the population) is available from the "Volkswirtschaftliche Gesamtrechnungen (VGR)" (= national economic calculations). We get the gdp ("BIP") for each administrative unit, which can be a county ('Landkreis'), a city ('kreisfreie Stadt'), or a city-state ('Stadtstaat', .e.g. Berlin, Hamburg). Note: the administrative disctinction into these three units is not trivial, e.g. http://de.wikipedia.org/wiki/Liste_der_kreisfreien_St%C3%A4dte_in_Deutschland 4 | 5 | https://www.destatis.de/DE/Publikationen/Thematisch/VolkswirtschaftlicheGesamtrechnungen/VGRderLaender/VGR_KreisergebnisseBand1.html 6 | 7 | We make two tables: 8 | - GERcounty: all entities which are NUTS3-regions (Landkreis, kreisfreie Stadt, Stadtstaat) 9 | - GERcity: all NUTS3-regions which contain at least one of the strings {'Kreisfreie Stadt', 'Stadt', 'Landeshauptstadt'} or are Berlin or Hamburg (these are citystates). Note that the third city-state Bremen is officially divided into two distinct NUTS3-regions, Bremen and Bremerhaven. 10 | 11 | 12 | Original analysis: May 2019 in repository spatial-cities. 13 | -------------------------------------------------------------------------------- /data/germany/__init__.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | 3 | def gdp(): 4 | f=open("../data/germany/GERcity_gdp_pop_2012","r") 5 | 6 | line=f.readline() 7 | line=f.readline() 8 | x=[] 9 | y=[] 10 | while len(line)>1: 11 | entry=line.strip("\n").split("\t") 12 | x.append(int(entry[1])) 13 | y.append(int(entry[2])) 14 | line=f.readline() 15 | return np.array(x),np.array(y) 16 | -------------------------------------------------------------------------------- /data/new_dataset/__init__.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | 3 | 4 | def index(): 5 | v = [] 6 | with open('../data/new_dataset/generic_dataset.txt', 'r') as f: 7 | for line in f: 8 | if line[0] == '#': 9 | continue 10 | line = line.strip("\n").split(',') # split data 11 | v.append(list(map(int, line[1:]))) 12 | v = np.array(v).transpose() 13 | return v[0, :], v[1, :] 14 | -------------------------------------------------------------------------------- /data/new_dataset/__init__.py~: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | 3 | 4 | def index(): 5 | v = [] 6 | with open('new_dataset/generic_dataset.txt', 'r') as f: 7 | for line in f: 8 | if line[0] == '#': 9 | continue 10 | line = line.strip("\n").split(',') # split data 11 | v.append(list(map(int, line[1:]))) 12 | v = np.array(v).transpose() 13 | return v[0, :], v[1, :] 14 | -------------------------------------------------------------------------------- /data/new_dataset/__pycache__/__init__.cpython-35.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/new_dataset/__pycache__/__init__.cpython-35.pyc -------------------------------------------------------------------------------- /data/new_dataset/__pycache__/__init__.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/new_dataset/__pycache__/__init__.cpython-36.pyc -------------------------------------------------------------------------------- /data/new_dataset/__pycache__/__init__.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/new_dataset/__pycache__/__init__.cpython-38.pyc -------------------------------------------------------------------------------- /data/new_dataset/generic_dataset.txt: -------------------------------------------------------------------------------- 1 | # city,population,Number_of_cinema_seats_(total_capacity) 2 | Berlin,3460725,50170 3 | Madrid,3198645,62005 4 | Hamburg,1786448,18912 5 | Warszawa,1708491,30327 6 | Barcelona,1611013,46693 7 | München,1353186,14989 8 | Praha,1241664,19900 9 | Wuppertal,349721,3134 10 | Murcia,437667,9423 11 | Szczecin,409596,3618 12 | Palma_de_Mallorca,402044,8377 13 | Tallinn,393222,5056 14 | Las_Palmas,381271,9214 15 | Brno,378965,3800 16 | Sintra,377680,2634 17 | Liège,377263,7775 18 | Bochum,374737,6118 19 | Zürich,372857,10748 20 | Bydgoszcz,363020,4943 21 | Bilbao,351356,4943 22 | Wuppertal,349721,3134 23 | Lublin,348567,2574 24 | Plovdiv,338062,2408 25 | Varna,334486,3541 26 | Alicante/Alacant,329325,9829 27 | Córdoba,328326,7649 28 | Bonn,324899,4586 29 | Bielefeld,323270,6241 30 | Mannheim,313174,4622 31 | -------------------------------------------------------------------------------- /data/new_dataset2/__init__.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | 3 | 4 | def index(): 5 | v = [] 6 | with open('../data/new_dataset2/generic_dataset.txt', 'r') as f: 7 | for line in f: 8 | if line[0] == '#': 9 | continue 10 | line = line.strip("\n").split(',') # split data 11 | try: 12 | v.append(list(map(float, line[:]))) 13 | except: 14 | print("Warning, ignoring line: ",line) 15 | v = np.array(v).transpose() 16 | return v[0, :], v[1, :] 17 | -------------------------------------------------------------------------------- /data/new_dataset2/__init__.py~: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | 3 | 4 | def index(): 5 | v = [] 6 | with open('new_dataset2/generic_dataset.txt', 'r') as f: 7 | for line in f: 8 | if line[0] == '#': 9 | continue 10 | line = line.strip("\n").split(',') # split data 11 | try: 12 | v.append(list(map(float, line[:]))) 13 | except: 14 | print("Warning, ignoring line: ",line) 15 | v = np.array(v).transpose() 16 | return v[0, :], v[1, :] 17 | -------------------------------------------------------------------------------- /data/new_dataset2/__pycache__/__init__.cpython-35.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/new_dataset2/__pycache__/__init__.cpython-35.pyc -------------------------------------------------------------------------------- /data/new_dataset2/__pycache__/__init__.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/new_dataset2/__pycache__/__init__.cpython-36.pyc -------------------------------------------------------------------------------- /data/new_dataset2/__pycache__/__init__.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/new_dataset2/__pycache__/__init__.cpython-38.pyc -------------------------------------------------------------------------------- /data/oecd/Readme: -------------------------------------------------------------------------------- 1 | downloaded from 2 | http://www.oecd-ilibrary.org/urban-rural-and-regional-development/data/oecd-regional-statistics_region-data-en 3 | 4 | OECD Regional Statistics 5 | Metropolitan areas 6 | -------------------------------------------------------------------------------- /data/oecd/__init__.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | 3 | def gdp(): 4 | f=open("../data/oecd/OECD_gdp_pop_2010","r") 5 | 6 | line=f.readline() 7 | line=f.readline() 8 | x=[] 9 | y=[] 10 | while len(line)>1: 11 | entry=line.strip("\n").split("\t") 12 | x.append(int(entry[1])) 13 | y.append(float(entry[2])) 14 | line=f.readline() 15 | return np.array(x),np.array(y) 16 | 17 | def patents(): 18 | f=open("../data/oecd/OECD_patents_pop_2008","r") 19 | 20 | line=f.readline() 21 | line=f.readline() 22 | x=[] 23 | y=[] 24 | while len(line)>1: 25 | entry=line.strip("\n").split("\t") 26 | x.append(int(entry[1])) 27 | y.append(float(entry[2])) 28 | line=f.readline() 29 | return np.array(x),np.array(y) 30 | 31 | -------------------------------------------------------------------------------- /data/oecd/__init__.py~: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | 3 | def gdp(): 4 | f=open("oecd/OECD_gdp_pop_2010","r") 5 | 6 | line=f.readline() 7 | line=f.readline() 8 | x=[] 9 | y=[] 10 | while len(line)>1: 11 | entry=line.strip("\n").split("\t") 12 | x.append(int(entry[1])) 13 | y.append(float(entry[2])) 14 | line=f.readline() 15 | return np.array(x),np.array(y) 16 | 17 | def patents(): 18 | f=open("oecd/OECD_patents_pop_2008","r") 19 | 20 | line=f.readline() 21 | line=f.readline() 22 | x=[] 23 | y=[] 24 | while len(line)>1: 25 | entry=line.strip("\n").split("\t") 26 | x.append(int(entry[1])) 27 | y.append(float(entry[2])) 28 | line=f.readline() 29 | return np.array(x),np.array(y) 30 | 31 | -------------------------------------------------------------------------------- /data/oecd/__pycache__/__init__.cpython-35.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/oecd/__pycache__/__init__.cpython-35.pyc -------------------------------------------------------------------------------- /data/oecd/__pycache__/__init__.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/oecd/__pycache__/__init__.cpython-36.pyc -------------------------------------------------------------------------------- /data/oecd/__pycache__/__init__.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/oecd/__pycache__/__init__.cpython-38.pyc -------------------------------------------------------------------------------- /data/uk/__init__.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | 3 | 4 | def row(rowname): 5 | f = open("../data/uk/raw_data/SumsP50D14F30.txt", "r") 6 | line = f.readline() 7 | entry = line.strip("\n").split("\t") 8 | rowfixed = 0 9 | for i in range(len(entry)): 10 | if entry[i] == rowname: 11 | rowfixed = i 12 | 13 | if rowfixed == 0: 14 | print('Wrong name: ', rowname, '\n Available are: \n d_Work AgricultHF Manufact Construct HotelRest FinanceInt RealEstate Admin Education Income NetIncome NIncBH NIncAH Households CarsVans Dwellings OccuDwell UnDwell UnSecDwell Employed Managers Profess technical Admin2 SkillTrd Service Sales plant Basic Coach Train Patents Morphology') 15 | return 0 16 | 17 | line = f.readline() 18 | x = [] 19 | y = [] 20 | while len(line) > 1: 21 | entry = line.strip("\n").split("\t") 22 | x.append(int(float(entry[1]))) 23 | y.append(float(entry[rowfixed])) 24 | line = f.readline() 25 | return np.array(x), np.array(y) 26 | -------------------------------------------------------------------------------- /data/uk/__init__.py~: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | 3 | 4 | def row(rowname): 5 | f = open("uk/raw_data/SumsP50D14F30.txt", "r") 6 | line = f.readline() 7 | entry = line.strip("\n").split("\t") 8 | rowfixed = 0 9 | for i in range(len(entry)): 10 | if entry[i] == rowname: 11 | rowfixed = i 12 | 13 | if rowfixed == 0: 14 | print('Wrong name: ', rowname, '\n Available are: \n d_Work AgricultHF Manufact Construct HotelRest FinanceInt RealEstate Admin Education Income NetIncome NIncBH NIncAH Households CarsVans Dwellings OccuDwell UnDwell UnSecDwell Employed Managers Profess technical Admin2 SkillTrd Service Sales plant Basic Coach Train Patents Morphology') 15 | return 0 16 | 17 | line = f.readline() 18 | x = [] 19 | y = [] 20 | while len(line) > 1: 21 | entry = line.strip("\n").split("\t") 22 | x.append(int(float(entry[1]))) 23 | y.append(float(entry[rowfixed])) 24 | line = f.readline() 25 | return np.array(x), np.array(y) 26 | -------------------------------------------------------------------------------- /data/uk/__pycache__/__init__.cpython-35.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/uk/__pycache__/__init__.cpython-35.pyc -------------------------------------------------------------------------------- /data/uk/__pycache__/__init__.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/uk/__pycache__/__init__.cpython-36.pyc -------------------------------------------------------------------------------- /data/uk/__pycache__/__init__.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/uk/__pycache__/__init__.cpython-38.pyc -------------------------------------------------------------------------------- /data/usa/Readme.md: -------------------------------------------------------------------------------- 1 | 2 | Files: 3 | 4 | 1) 5 | USA-location.csv 6 | Latitute and longitude of the 381 metropolitan areas. Manual inspection using online maps reveal that the location is typically at the centre of the largest city. 7 | 8 | 9 | 2) USmetro_gdp_pop_2013 10 | From previous paper 11 | 381 Metropolitan areas, different from 1); 12 | population and gdp 13 | States 14 | 15 | 3) metropolitan-miles.csv 16 | from previous paper 17 | Same file seems to be online at: 18 | https://www.fhwa.dot.gov/policyinformation/statistics/2013/pdf/hm71.pdf 19 | 20 | 484 metropolitan areas, population and miles 21 | 22 | 23 | Merge: 24 | 25 | To attribute location to each city, the information in file 1 was added to files 2 and 3. In case of file 2, this was straightforward as both cases correspond to the same metropolitan areas. In the case of file 3, this was done with some manual input. The output was a new file: 26 | 27 | 4) miles-location.csv 28 | Contains Road length and location of 362 metropolitan areas in the USA, obtained after merging files 1 and 3 as described above. 29 | 30 | 31 | 32 | 33 | 34 | -------------------------------------------------------------------------------- /data/usa/__init__.py~: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | 3 | 4 | def gdp(): 5 | f=open("usa/USmetro_gdp_pop_2013","r") 6 | 7 | line=f.readline() 8 | line=f.readline() 9 | x=[] 10 | y=[] 11 | while len(line)>1: 12 | entry=line.strip("\n").split("\t") 13 | x.append(int(entry[1])) 14 | y.append(float(entry[2])) 15 | line=f.readline() 16 | return np.array(x),np.array(y) 17 | 18 | 19 | def miles(): 20 | f=open("usa/metropolitan-miles.csv","r") 21 | line=f.readline() 22 | x=[] 23 | y=[] 24 | while len(line)>1: 25 | # print 'oi:',line,'->', 26 | line=line[1:-2] 27 | entry=line.strip("\n").split('",') 28 | if len(entry)==3: 29 | xe=entry[1].strip(" ").replace(',','') 30 | ye=entry[2].strip(" ").replace(',','') 31 | if not xe.isalnum(): 32 | xe=xe[1:] 33 | if not ye.isalnum(): 34 | ye=ye[1:] 35 | # print "mid",xe,ye,len(xe),len(ye) 36 | if len(xe)>0 and len(ye)>0: 37 | x.append(int(xe)) 38 | y.append(float(ye)) 39 | # else: 40 | # print 'Not added 2',line 41 | # else: 42 | # print 'Not added:',line 43 | # print xe,ye 44 | line=f.readline() 45 | return np.array(x),np.array(y) 46 | -------------------------------------------------------------------------------- /data/usa/__pycache__/__init__.cpython-35.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/usa/__pycache__/__init__.cpython-35.pyc -------------------------------------------------------------------------------- /data/usa/__pycache__/__init__.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/usa/__pycache__/__init__.cpython-36.pyc -------------------------------------------------------------------------------- /data/usa/__pycache__/__init__.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/usa/__pycache__/__init__.cpython-38.pyc -------------------------------------------------------------------------------- /data/usa/raw_data/US_metro_pop_2013.xls: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/usa/raw_data/US_metro_pop_2013.xls -------------------------------------------------------------------------------- /data/usa/raw_data/hm71.xls: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/data/usa/raw_data/hm71.xls -------------------------------------------------------------------------------- /notebooks/__pycache__/analysis.cpython-35.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/notebooks/__pycache__/analysis.cpython-35.pyc -------------------------------------------------------------------------------- /notebooks/__pycache__/analysis.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/notebooks/__pycache__/analysis.cpython-36.pyc -------------------------------------------------------------------------------- /notebooks/__pycache__/best_parameters.cpython-35.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/notebooks/__pycache__/best_parameters.cpython-35.pyc -------------------------------------------------------------------------------- /notebooks/__pycache__/best_parameters.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/notebooks/__pycache__/best_parameters.cpython-36.pyc -------------------------------------------------------------------------------- /notebooks/__pycache__/pvalue_population.cpython-35.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/notebooks/__pycache__/pvalue_population.cpython-35.pyc -------------------------------------------------------------------------------- /notebooks/__pycache__/pvalue_population.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/notebooks/__pycache__/pvalue_population.cpython-36.pyc -------------------------------------------------------------------------------- /notebooks/_results/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/notebooks/_results/.DS_Store -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDAnalysis_covid19_brazil_2_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 43692.12642207937, 3 | "errors": [ 4 | 0.010696200664074788, 5 | 0.011000593027327657, 6 | 0.12311390527366949, 7 | 0.02794084205244125 8 | ], 9 | "params": [ 10 | 0.10337621793912789, 11 | 0.9965656530239487, 12 | 0.5894802401143214, 13 | 0.9687759978484156 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDAnalysis_eurostat_cinema_attendance_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3124.4963310334115, 3 | "errors": [ 4 | 0.80098441316029267, 5 | 0.11232948355454689, 6 | 37.586585251032687, 7 | 0.11315353738555842 8 | ], 9 | "params": [ 10 | 0.51280863479836936, 11 | 1.1347752221505285, 12 | 16.039891097462419, 13 | 0.76528587171985418 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDAnalysis_eurostat_cinema_seats_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3668.4228440740007, 3 | "errors": [ 4 | 0.051283419961088775, 5 | 0.059556419071890292, 6 | 12.428363229210175, 7 | 0.13027095487310919 8 | ], 9 | "params": [ 10 | 0.050102776547392591, 11 | 0.91621465147108083, 12 | 9.3752118628569523, 13 | 0.64876409663230383 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDAnalysis_eurostat_libraries_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 2050.2160828609531, 3 | "errors": [ 4 | 0.0011488119610542195, 5 | 0.082735496268457692, 6 | 0.27873438455925548, 7 | 0.1306146075223113 8 | ], 9 | "params": [ 10 | 0.0010602177657929297, 11 | 0.77968961603615239, 12 | 0.91996545548645048, 13 | 0.84014826014754684 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDAnalysis_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 6343.6165414904917, 3 | "errors": [ 4 | 0.10894922364769527, 5 | 0.22025294655914318, 6 | 123.8575486484323, 7 | 0.22921160166549903 8 | ], 9 | "params": [ 10 | 0.013079107490151981, 11 | 1.3859624682946234, 12 | 38.10492520598536, 13 | 0.75802122653833603 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDAnalysis_eurostat_theaters_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 996.95143678412251, 3 | "errors": [ 4 | 3.4993776291144317e-05, 5 | 0.18709815582580042, 6 | 0.11195158571661307, 7 | 0.0 8 | ], 9 | "params": [ 10 | 3.9505678235886292e-06, 11 | 1.143118015340103, 12 | 0.81950495666189327, 13 | 1.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDAnalysis_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 2991.8172106702232, 3 | "errors": [ 4 | 0.0036490445977762111, 5 | 0.048375170750964119, 6 | 0.4389932471109434, 7 | 0.069120173137597454 8 | ], 9 | "params": [ 10 | 0.0054687041189707608, 11 | 1.1254294709092036, 12 | 0.32733884575809524, 13 | 1.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDAnalysis_ocde_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1504.6888707366893, 3 | "errors": [ 4 | 0.00015615705274952204, 5 | 0.2119092018512308, 6 | 9.7801293923467103, 7 | 0.30243686713727469 8 | ], 9 | "params": [ 10 | 2.2900517934182353e-05, 11 | 1.1337297273236617, 12 | 4.2004994973279333, 13 | 0.78051655190334923 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDAnalysis_uk_income_16_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1698.9214313988734, 3 | "errors": [ 4 | 180.4906828447517, 5 | 0.04725639625218613, 6 | 79.25696979791671, 7 | 0.3208851627373398 8 | ], 9 | "params": [ 10 | 304.7352273243427, 11 | 0.9727850982928572, 12 | 0.17114949574200125, 13 | 1.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDAnalysis_uk_income_1_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1702.0657554699144, 3 | "errors": [ 4 | 593.0330643876022, 5 | 0.127054400756415, 6 | 222.7694481176243, 7 | 0.2858855510790481 8 | ], 9 | "params": [ 10 | 179.61748674960046, 11 | 1.0163825607795758, 12 | 0.5127953782907235, 13 | 0.9389479690871194 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDAnalysis_uk_income_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1698.9214313873986, 3 | "errors": [ 4 | 190.48089424820046, 5 | 0.047197205199417919, 6 | 40.649496081306104, 7 | 0.31462927438154936 8 | ], 9 | "params": [ 10 | 304.72621803515375, 11 | 0.97278744731167588, 12 | 0.17114974711599473, 13 | 1.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDAnalysis_uk_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 609.12765035463769, 3 | "errors": [ 4 | 0.0044275071677268478, 5 | 0.27489610439450213, 6 | 4.0972770048322058, 7 | 0.2781192885164811 8 | ], 9 | "params": [ 10 | 0.0018836002331406581, 11 | 0.95702336868180071, 12 | 2.0430813766645723, 13 | 0.85402520826144224 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDAnalysis_uk_train_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 218.82705906890283, 3 | "errors": [ 4 | 2.9987562332114094e-05, 5 | 0.11602561992497966, 6 | 0.16957192324100132, 7 | 0.17848106355762311 8 | ], 9 | "params": [ 10 | 1.4939015983111738e-05, 11 | 1.0451096171089995, 12 | 0.56975948286372691, 13 | 1.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDAnalysis_usa_gdp_1_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3709.9782507437, 3 | "errors": [ 4 | 0.003276338568775449, 5 | 0.02498969731376299, 6 | 5.127512054278163, 7 | 0.15300516378715567 8 | ], 9 | "params": [ 10 | 0.010205850719102396, 11 | 1.115960499074923, 12 | 0.9276596886379637, 13 | 0.879258832380629 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDAnalysis_usa_gdp_2_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3709.9782507901955, 3 | "errors": [ 4 | 0.0032859757457757836, 5 | 0.02410129843011141, 6 | 2.413030931885206, 7 | 0.14062345994716544 8 | ], 9 | "params": [ 10 | 0.01020563707529006, 11 | 1.115962005652085, 12 | 0.9276547583290445, 13 | 0.8792591453312284 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDAnalysis_usa_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3709.9782507249124, 3 | "errors": [ 4 | 0.0029980897170135156, 5 | 0.021637508362574824, 6 | 1.5014713230860941, 7 | 0.12080083056488322 8 | ], 9 | "params": [ 10 | 0.010206264787128903, 11 | 1.1159572729641911, 12 | 0.92763443560213965, 13 | 0.87926172523002699 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDAnalysis_usa_miles_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3519.8699243438386, 3 | "errors": [ 4 | 0.029161335593210016, 5 | 0.036144694270709349, 6 | 9.5370167966768431, 7 | 0.18517694654523831 8 | ], 9 | "params": [ 10 | 0.064867626229607817, 11 | 0.81380015099782277, 12 | 6.0445106406320948, 13 | 0.63205860620380949 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDAnalysis_usa_miles_8_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3519.86992434475, 3 | "errors": [ 4 | 0.03120485066943391, 5 | 0.03831691091346532, 6 | 8.97699972924946, 7 | 0.2094422572175193 8 | ], 9 | "params": [ 10 | 0.06486750300520464, 11 | 0.8138002902702632, 12 | 6.0445662165737915, 13 | 0.63205735629487 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDFixedBetaAnalysis_covid19_brazil_2_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 43692.328283513976, 3 | "errors": [ 4 | 0.0011114163375696095, 5 | 0.0, 6 | 0.15227715742380268, 7 | 0.03177482392101075 8 | ], 9 | "params": [ 10 | 0.10003005175428276, 11 | 1.0, 12 | 0.6080658939456866, 13 | 0.9645032335257907 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDFixedBetaAnalysis_eurostat_cinema_attendance_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3128.6201820181668, 3 | "errors": [ 4 | 0.33356935931403225, 5 | 0.0, 6 | 35.026347527928202, 7 | 0.17422693910684356 8 | ], 9 | "params": [ 10 | 2.7133780469886926, 11 | 1.0, 12 | 5.9290573564185207, 13 | 0.84050105471803205 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDFixedBetaAnalysis_eurostat_cinema_seats_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3673.1942432003621, 3 | "errors": [ 4 | 0.0010649619625625645, 5 | 0.0, 6 | 19.138361292360141, 7 | 0.12024815096995778 8 | ], 9 | "params": [ 10 | 0.017549462479074147, 11 | 1.0, 12 | 15.930862753280394, 13 | 0.58701432984723245 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDFixedBetaAnalysis_eurostat_libraries_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 2077.7701246431593, 3 | "errors": [ 4 | 4.8337293067110496e-06, 5 | 0.0, 6 | 0.53303427641644729, 7 | 0.1307652737398276 8 | ], 9 | "params": [ 10 | 6.9821709973872832e-05, 11 | 1.0, 12 | 1.5015120192548697, 13 | 0.68417649528912972 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDFixedBetaAnalysis_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 6352.3981829364002, 3 | "errors": [ 4 | 0.27860995558185508, 5 | 0.0, 6 | 3.2417146515537794, 7 | 0.067490780066302616 8 | ], 9 | "params": [ 10 | 1.3940004666412364, 11 | 1.0, 12 | 1.9057160601343426, 13 | 1.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDFixedBetaAnalysis_eurostat_theaters_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1007.9488208563797, 3 | "errors": [ 4 | 1.7504667960465312e-06, 5 | 0.0, 6 | 0.16403191376373097, 7 | 0.02651150528216533 8 | ], 9 | "params": [ 10 | 2.1873903181364037e-05, 11 | 1.0, 12 | 0.84854486011512575, 13 | 1.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDFixedBetaAnalysis_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3006.2877014285523, 3 | "errors": [ 4 | 0.0014548628209270905, 5 | 0.0, 6 | 0.03229452129517265, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.031913037738656884, 11 | 1.0, 12 | 0.34343049036383133, 13 | 1.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDFixedBetaAnalysis_ocde_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1505.885154927289, 3 | "errors": [ 4 | 2.6473906062981833e-05, 5 | 0.0, 6 | 7.6149034479455677, 7 | 0.27850587699974866 8 | ], 9 | "params": [ 10 | 0.00015330367827187389, 11 | 1.0, 12 | 2.3433207364548529, 13 | 0.88914426337621477 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDFixedBetaAnalysis_uk_income_16_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1700.185095550793, 3 | "errors": [ 4 | 8.353250966089641, 5 | 0.0, 6 | 18.540642230561623, 7 | 0.17886388508102544 8 | ], 9 | "params": [ 10 | 219.8472623487793, 11 | 1.0, 12 | 0.32196939970553046, 13 | 0.9643621428038236 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDFixedBetaAnalysis_uk_income_1_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 2010.2415604973378, 3 | "errors": [ 4 | 1673.6407597075774, 5 | 0.0, 6 | 292.0690719937093, 7 | 0.3792004701681437 8 | ], 9 | "params": [ 10 | 1067.0481019881267, 11 | 1.0, 12 | 0.7943795904752284, 13 | 1.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDFixedBetaAnalysis_uk_income_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1700.1850955499283, 3 | "errors": [ 4 | 9.284036537323459, 5 | 0.0, 6 | 67.91781557987251, 7 | 0.20679703986752404 8 | ], 9 | "params": [ 10 | 219.84735331687818, 11 | 1.0, 12 | 0.32195839140129079, 13 | 0.96436406311449852 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDFixedBetaAnalysis_uk_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 609.26872672476929, 3 | "errors": [ 4 | 0.00022758541608485571, 5 | 0.0, 6 | 3.9507359197076775, 7 | 0.25947513496405189 8 | ], 9 | "params": [ 10 | 0.0011044243587074044, 11 | 1.0, 12 | 2.6140573831233493, 13 | 0.80977470867787149 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDFixedBetaAnalysis_uk_train_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 219.48589182817113, 3 | "errors": [ 4 | 3.1275254893788606e-06, 5 | 0.0, 6 | 0.079792150208387369, 7 | 0.094447700169576362 8 | ], 9 | "params": [ 10 | 2.5663226458852794e-05, 11 | 1.0, 12 | 0.57304782687321376, 13 | 1.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDFixedBetaAnalysis_usa_gdp_1_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3745.1510665814862, 3 | "errors": [ 4 | 0.0015226162569935673, 5 | 0.0, 6 | 0.1434459122021807, 7 | 0.02419719142778791 8 | ], 9 | "params": [ 10 | 0.04469582079896927, 11 | 1.0, 12 | 0.3185591243052197, 13 | 1.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDFixedBetaAnalysis_usa_gdp_2_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3745.1510665814912, 3 | "errors": [ 4 | 0.00149530837186824, 5 | 0.0, 6 | 0.09972691333535028, 7 | 0.015321746105187693 8 | ], 9 | "params": [ 10 | 0.04469582024748971, 11 | 1.0, 12 | 0.3185591023187461, 13 | 1.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDFixedBetaAnalysis_usa_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3745.1510665814581, 3 | "errors": [ 4 | 0.0015795400271780863, 5 | 0.0, 6 | 0.10600545921246078, 7 | 0.017935014775645294 8 | ], 9 | "params": [ 10 | 0.044695825779157428, 11 | 1.0, 12 | 0.31855906529737088, 13 | 1.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDFixedBetaAnalysis_usa_miles_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3606.1617017824774, 3 | "errors": [ 4 | 0.0010030763430021023, 5 | 0.0, 6 | 11.861310734286045, 7 | 0.24085156316034001 8 | ], 9 | "params": [ 10 | 0.0057401977467526413, 11 | 1.0, 12 | 6.1146806721674594, 13 | 0.67513877824789559 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_ConstrainedDFixedBetaAnalysis_usa_miles_8_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3606.1617017832186, 3 | "errors": [ 4 | 0.0008971385838002714, 5 | 0.0, 6 | 13.802310842921178, 7 | 0.22334408681914267 8 | ], 9 | "params": [ 10 | 0.005740193461709018, 11 | 1.0, 12 | 6.114673186925629, 13 | 0.675138905812729 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDAnalysis_eurostat_cinema_attendance_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3138.4449094698998, 3 | "errors": [ 4 | 0.91163766420634662, 5 | 0.1336156924693076, 6 | 68.9374733097453, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.56438781701108032, 11 | 1.1253875253252059, 12 | 541.23812837870082, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDAnalysis_eurostat_cinema_seats_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3672.9672963648491, 3 | "errors": [ 4 | 0.037810735122349129, 5 | 0.073854357824013089, 6 | 3.624379256060716, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.031909211413450024, 11 | 0.95196325126451264, 12 | 31.063309122411621, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDAnalysis_eurostat_libraries_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 2090.4944256942495, 3 | "errors": [ 4 | 0.0010006833223277234, 5 | 0.14262908982908395, 6 | 0.29206670771790322, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.00033303879674589839, 11 | 0.87132798242689369, 12 | 2.3712625108235241, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDAnalysis_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 6362.6034917037214, 3 | "errors": [ 4 | 0.0097968212260098261, 5 | 0.33509981568287334, 6 | 707.32030941715232, 7 | 0.0 8 | ], 9 | "params": [ 10 | 4.4948350179007791e-05, 11 | 1.8045333217682671, 12 | 1302.8419587493197, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDAnalysis_eurostat_theaters_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1107.0671237213446, 3 | "errors": [ 4 | 5.4262638439927127e-06, 5 | 0.29557841227533771, 6 | 1.0358665621572691, 7 | 0.0 8 | ], 9 | "params": [ 10 | 4.7687735531219646e-08, 11 | 1.4672838720505634, 12 | 2.6720109613739567, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDAnalysis_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3074.6910181576509, 3 | "errors": [ 4 | 0.011083506123110168, 5 | 0.082398920111078369, 6 | 18.122232029742175, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.0084541052638499974, 11 | 1.0934023640254633, 12 | 88.233573049562978, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDAnalysis_ocde_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1519.2270683321881, 3 | "errors": [ 4 | 0.00017517033412777749, 5 | 0.33438818384680719, 6 | 7.3615134324368041, 7 | 0.0 8 | ], 9 | "params": [ 10 | 2.3362141691456797e-06, 11 | 1.2798491993669721, 12 | 21.654703037325419, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDAnalysis_uk_income_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1739.5192555062506, 3 | "errors": [ 4 | 416.73711420947257, 5 | 0.15294863378700238, 6 | 849.8508567269547, 7 | 0.0 8 | ], 9 | "params": [ 10 | 88.661890468744375, 11 | 1.0678566031639538, 12 | 1568.9951222594982, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDAnalysis_uk_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 613.09547698147492, 3 | "errors": [ 4 | 0.0077037022370567716, 5 | 0.25699529447597547, 6 | 7.9292640382321036, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.00040931712440796909, 11 | 1.0710627709618057, 12 | 14.427794842861118, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDAnalysis_uk_train_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 233.70220076702321, 3 | "errors": [ 4 | 6.2307991744468652e-06, 5 | 0.10104017770952053, 6 | 0.36645629212016495, 7 | 0.0 8 | ], 9 | "params": [ 10 | 1.6542286549783694e-06, 11 | 1.2135917760900765, 12 | 1.4666718686728815, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDAnalysis_usa_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3810.7721077182596, 3 | "errors": [ 4 | 0.0027319108333695853, 5 | 0.03045830377642236, 6 | 9.1119452876418965, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.0072783163876335008, 11 | 1.1395129247833238, 12 | 46.056858517525313, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDAnalysis_usa_miles_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3532.2359247024137, 3 | "errors": [ 4 | 0.033385978898914384, 5 | 0.043287464746677551, 6 | 3.4188807245790547, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.060227843212396173, 11 | 0.81909103228124247, 12 | 15.819973721133861, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDFixedBetaAnalysis_eurostat_cinema_attendance_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3144.3363729452949, 3 | "errors": [ 4 | 0.2932443708354921, 5 | 0.0, 6 | 57.690446053838578, 7 | 0.0 8 | ], 9 | "params": [ 10 | 2.929824361330128, 11 | 1.0, 12 | 518.95304148116384, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDFixedBetaAnalysis_eurostat_cinema_seats_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3675.3353546429516, 3 | "errors": [ 4 | 0.0010197461138244726, 5 | 0.0, 6 | 3.7099183996197698, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.017298835001223471, 11 | 1.0, 12 | 31.89635994019611, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDFixedBetaAnalysis_eurostat_libraries_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 2103.2076669579747, 3 | "errors": [ 4 | 5.4979078741602644e-06, 5 | 0.0, 6 | 0.26772224611170842, 7 | 0.0 8 | ], 9 | "params": [ 10 | 6.476005164920211e-05, 11 | 1.0, 12 | 2.540143968100975, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDFixedBetaAnalysis_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 6510.1473617241518, 3 | "errors": [ 4 | 0.65084028816410822, 5 | 0.0, 6 | 246.72547391082782, 7 | 0.0 8 | ], 9 | "params": [ 10 | 2.1692989032704126, 11 | 1.0, 12 | 1009.9856755658631, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDFixedBetaAnalysis_eurostat_theaters_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1166.7359195674717, 3 | "errors": [ 4 | 3.3942727660037849e-06, 5 | 0.0, 6 | 0.65499883890283517, 7 | 0.0 8 | ], 9 | "params": [ 10 | 2.3177545310892116e-05, 11 | 1.0, 12 | 2.327269861666625, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDFixedBetaAnalysis_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3091.2472862975665, 3 | "errors": [ 4 | 0.0030340211833439945, 5 | 0.0, 6 | 16.330295166605605, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.03499046341051492, 11 | 1.0, 12 | 88.680179367099441, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDFixedBetaAnalysis_ocde_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1531.8617416954085, 3 | "errors": [ 4 | 3.5601461081933884e-05, 5 | 0.0, 6 | 5.4871551958346698, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.00017133874363428665, 11 | 1.0, 12 | 19.003957659051412, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDFixedBetaAnalysis_uk_income_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1758.8756747388318, 3 | "errors": [ 4 | 33.623467935563582, 5 | 0.0, 6 | 961.05306333904082, 7 | 0.0 8 | ], 9 | "params": [ 10 | 228.14266595961863, 11 | 1.0, 12 | 1779.9121091178135, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDFixedBetaAnalysis_uk_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 614.57021841290032, 3 | "errors": [ 4 | 0.00022272989426882006, 5 | 0.0, 6 | 7.4455491213261258, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.0011058827903206324, 11 | 1.0, 12 | 13.640021979784953, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDFixedBetaAnalysis_uk_train_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 267.29979496975761, 3 | "errors": [ 4 | 9.7658160702244483e-06, 5 | 0.0, 6 | 0.46355379378580158, 7 | 0.0 8 | ], 9 | "params": [ 10 | 3.3800020687518906e-05, 11 | 1.0, 12 | 1.6466267405284107, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDFixedBetaAnalysis_usa_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3934.7391504242237, 3 | "errors": [ 4 | 0.0038140839290554162, 5 | 0.0, 6 | 8.3838589160528691, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.055794207757093081, 11 | 1.0, 12 | 55.710294919217148, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_FixedDFixedBetaAnalysis_usa_miles_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3631.0358762753149, 3 | "errors": [ 4 | 0.00059916405948848934, 5 | 0.0, 6 | 6.2141003292778754, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.0048316999467762078, 11 | 1.0, 12 | 23.366679428156289, 13 | 0.5 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_covid19_brazil_2_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 43845.90346580128, 3 | "errors": [ 4 | 0.011360892352107414, 5 | 0.011024820975600974, 6 | 0.12043992108567848, 7 | 0.05539807812327989 8 | ], 9 | "params": [ 10 | 0.10915987383687448, 11 | 0.9932655871602741, 12 | 0.3001370412931239, 13 | 2.0230540453885997 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_eurostat_cinema_attendance_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3132.6727017122344, 3 | "errors": [ 4 | 6.1272512635252365, 5 | 0.29952378234326082, 6 | 5186168.0042308122, 7 | 0.81066759121370524 8 | ], 9 | "params": [ 10 | 4.2145412476637514, 11 | 1.001353985495969, 12 | 2971892.085130237, 13 | 1.047099727198685 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_eurostat_cinema_seats_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3653.5042431797451, 3 | "errors": [ 4 | 0.048986578661012845, 5 | 0.06291260429024205, 6 | 1172.3916174835422, 7 | 0.15540419577114803 8 | ], 9 | "params": [ 10 | 0.064651379460661532, 11 | 0.89900400394358226, 12 | 1255.1091166839294, 13 | 1.0453140298048116 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_eurostat_libraries_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 2073.1758843443499, 3 | "errors": [ 4 | 0.0010714118224304295, 5 | 0.088423485166313293, 6 | 1.1201725561097846, 7 | 0.44440807454881798 8 | ], 9 | "params": [ 10 | 0.00076902616888297425, 11 | 0.81387120224570431, 12 | 0.77667894437147644, 13 | 2.0879596379552083 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 5805.3345808781778, 3 | "errors": [ 4 | 0.083750494868298886, 5 | 0.1504495287744434, 6 | 325.37731908609146, 7 | 0.21915256692326449 8 | ], 9 | "params": [ 10 | 0.019882901620490695, 11 | 1.3509476119735069, 12 | 40.218085742875807, 13 | 1.7859055253912959 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_eurostat_theaters_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 805.98725423378096, 3 | "errors": [ 4 | 9.4238354999270351e-05, 5 | 0.10536836388805283, 6 | 0.079235749003556524, 7 | 0.27386034027024059 8 | ], 9 | "params": [ 10 | 5.6038792945616741e-05, 11 | 0.91965876433583715, 12 | 0.27576690077975635, 13 | 2.5070173778249365 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3029.4163676916578, 3 | "errors": [ 4 | 0.0049376007901305932, 5 | 0.04997470090103151, 6 | 2.9402588595566663, 7 | 0.2561562678835797 8 | ], 9 | "params": [ 10 | 0.0065481651021607893, 11 | 1.113464212350969, 12 | 0.39874196300964476, 13 | 1.922472552203657 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_ocde_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1370.9525138875165, 3 | "errors": [ 4 | 0.00037215827002483331, 5 | 0.2091514226876881, 6 | 3785.4087269217202, 7 | 0.89680287887008903 8 | ], 9 | "params": [ 10 | 4.4886338023471711e-05, 11 | 1.1238060226685112, 12 | 74.662135721412071, 13 | 1.7022723207801076 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_uk_income_15_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1695.028976906555, 3 | "errors": [ 4 | 9.042952464574688, 5 | 0.0, 6 | 277.8592710078924, 7 | 0.34627031467899777 8 | ], 9 | "params": [ 10 | 220.0579949760902, 11 | 1.0, 12 | 0.042808712491187534, 13 | 1.9759871733725825 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_uk_income_16_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1693.6093449830637, 3 | "errors": [ 4 | 206.64345460522722, 5 | 0.04728993911442571, 6 | 3137.51027593557, 7 | 0.7887766405596562 8 | ], 9 | "params": [ 10 | 312.4921084479437, 11 | 0.9706533800646346, 12 | 0.0248253638059936, 13 | 2.005794699103576 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_uk_income_1_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1693.6093450523438, 3 | "errors": [ 4 | 213.2071930333243, 5 | 0.09034386451602121, 6 | 3510.3001053303606, 7 | 0.7424218831495446 8 | ], 9 | "params": [ 10 | 312.42904267828317, 11 | 0.9706702315944166, 12 | 0.024834575947390667, 13 | 2.005776604313376 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_uk_income_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1693.6093448692677, 3 | "errors": [ 4 | 193.82208995897341, 5 | 0.044710650465402381, 6 | 7393.9909828319996, 7 | 0.70502269333179823 8 | ], 9 | "params": [ 10 | 312.46714281201571, 11 | 0.97066031759923599, 12 | 0.024835676261744752, 13 | 2.0057737932679718 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_uk_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 546.7126323568358, 3 | "errors": [ 4 | 0.0045764535845405985, 5 | 0.13107647803304961, 6 | 41.185953362891127, 7 | 0.53937542453720322 8 | ], 9 | "params": [ 10 | 0.0016327137336579959, 11 | 0.96603766666549595, 12 | 2.4679512218940358, 13 | 1.6746030129254568 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_uk_train_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 204.07562254651364, 3 | "errors": [ 4 | 3.75968282945477e-05, 5 | 0.10041496179735442, 6 | 0.17658855328654138, 7 | 0.34640003564103988 8 | ], 9 | "params": [ 10 | 1.8244927313711394e-05, 11 | 1.0289191091695258, 12 | 0.33317042308782946, 13 | 2.1106823386867184 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_usa_gdp_1_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3654.0678715719473, 3 | "errors": [ 4 | 0.25057551764194796, 5 | 0.11088301923522514, 6 | 298.1604813119517, 7 | 0.37578273978542426 8 | ], 9 | "params": [ 10 | 0.010592550781040518, 11 | 1.112979683393738, 12 | 0.1926731558901747, 13 | 1.8954492947010373 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_usa_gdp_2_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3654.06787126757, 3 | "errors": [ 4 | 0.0038403817531572895, 5 | 0.026156565104364895, 6 | 0.8180764087646459, 7 | 0.18586601926407467 8 | ], 9 | "params": [ 10 | 0.010591833375165921, 11 | 1.112985112095562, 12 | 0.19261113456135637, 13 | 1.8954873952607947 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_usa_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3654.0678712428839, 3 | "errors": [ 4 | 0.0034348181667698519, 5 | 0.024022009610325974, 6 | 0.833206145849961, 7 | 0.18440863962792739 8 | ], 9 | "params": [ 10 | 0.010592143186803311, 11 | 1.1129828415298892, 12 | 0.19260567154797745, 13 | 1.8954906225279899 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_usa_miles_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3425.5186237312878, 3 | "errors": [ 4 | 0.02351342918259032, 5 | 0.032962316815713613, 6 | 14.480926413852899, 7 | 0.21867834054234275 8 | ], 9 | "params": [ 10 | 0.06063877504588553, 11 | 0.81926301153194736, 12 | 4.4579779391930234, 13 | 1.5425384427269258 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalAnalysis_usa_miles_8_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3425.518623743283, 3 | "errors": [ 4 | 0.02524126263966741, 5 | 0.030904363670818037, 6 | 22.70592368630539, 7 | 0.27463617280121516 8 | ], 9 | "params": [ 10 | 0.06063900531303584, 11 | 0.8192628079796318, 12 | 4.457856083515378, 13 | 1.542541150268007 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedBetaAnalysis_covid19_brazil_2_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 43846.46216653026, 3 | "errors": [ 4 | 0.0012416298759777694, 5 | 0.0, 6 | 0.11381663320813304, 7 | 0.04944486356642578 8 | ], 9 | "params": [ 10 | 0.10243755404745455, 11 | 1.0, 12 | 0.2921699716923508, 13 | 2.0268567936810498 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedBetaAnalysis_eurostat_cinema_attendance_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3132.7256602795987, 3 | "errors": [ 4 | 1.0152675307084449, 5 | 0.0, 6 | 4181512.7891275622, 7 | 0.4710982888521188 8 | ], 9 | "params": [ 10 | 4.2777774345304183, 11 | 1.0, 12 | 1954452.7634112986, 13 | 1.0772003553405358 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedBetaAnalysis_eurostat_cinema_seats_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3658.9061045644735, 3 | "errors": [ 4 | 0.0012435688065665625, 5 | 0.0, 6 | 905.24248368749272, 7 | 0.24159466795140219 8 | ], 9 | "params": [ 10 | 0.018423900484042233, 11 | 1.0, 12 | 247.52138051584706, 13 | 1.240571253041751 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedBetaAnalysis_eurostat_libraries_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 2080.2410266880765, 3 | "errors": [ 4 | 6.1340020943674821e-06, 5 | 0.0, 6 | 0.55347010452404966, 7 | 0.3818696746834388 8 | ], 9 | "params": [ 10 | 8.4797756116059041e-05, 11 | 1.0, 12 | 0.60939917495540075, 13 | 2.1995080800576403 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedBetaAnalysis_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 5818.1380512580436, 3 | "errors": [ 4 | 0.2684235867624305, 5 | 0.0, 6 | 17733.493969896135, 7 | 0.26187193014250254 8 | ], 9 | "params": [ 10 | 1.519949613061127, 11 | 1.0, 12 | 1298.3920769672081, 13 | 1.5255566647719334 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedBetaAnalysis_eurostat_theaters_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 807.4198008690189, 3 | "errors": [ 4 | 1.7716667832639113e-06, 5 | 0.0, 6 | 0.097611648798176659, 7 | 0.285712806657762 8 | ], 9 | "params": [ 10 | 2.1828440565403364e-05, 11 | 1.0, 12 | 0.28470953903593499, 13 | 2.4968441098400911 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedBetaAnalysis_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3036.3830246153188, 3 | "errors": [ 4 | 0.0014786591522149596, 5 | 0.0, 6 | 35.011041524219273, 7 | 0.33721450853964952 8 | ], 9 | "params": [ 10 | 0.032749304342060338, 11 | 1.0, 12 | 1.3161801233542061, 13 | 1.8165336415281053 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedBetaAnalysis_ocde_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1371.1920231286144, 3 | "errors": [ 4 | 4.9723069767054314e-05, 5 | 0.0, 6 | 4000.3655640165412, 7 | 0.79250543905651361 8 | ], 9 | "params": [ 10 | 0.00026061694660571051, 11 | 1.0, 12 | 199.2186251042601, 13 | 1.539036028218199 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedBetaAnalysis_uk_income_16_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1695.0289769014355, 3 | "errors": [ 4 | 8.250577166979605, 5 | 0.0, 6 | 30.747122795975805, 7 | 0.2641266804194372 8 | ], 9 | "params": [ 10 | 220.05787017341984, 11 | 1.0, 12 | 0.04281827275872221, 13 | 1.9759750559213225 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedBetaAnalysis_uk_income_1_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1695.02897690189, 3 | "errors": [ 4 | 8.89420557075091, 5 | 0.0, 6 | 88.06040133760216, 7 | 0.4951929638795127 8 | ], 9 | "params": [ 10 | 220.05811318142892, 11 | 1.0, 12 | 0.04281795100647253, 13 | 1.9759753683406298 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedBetaAnalysis_uk_income_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1695.0289769014084, 3 | "errors": [ 4 | 8.2198444278555147, 5 | 0.0, 6 | 53.519039034556855, 7 | 0.32225829269088779 8 | ], 9 | "params": [ 10 | 220.05807744132107, 11 | 1.0, 12 | 0.042817613740157856, 13 | 1.975975850667542 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedBetaAnalysis_uk_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 546.92605813262378, 3 | "errors": [ 4 | 0.00019130806066135393, 5 | 0.0, 6 | 19.302396157240498, 7 | 0.36386949080161052 8 | ], 9 | "params": [ 10 | 0.0010753983421847948, 11 | 1.0, 12 | 2.1022065732705411, 13 | 1.7038877279269289 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedBetaAnalysis_uk_train_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 204.16980657118822, 3 | "errors": [ 4 | 3.0006229372392087e-06, 5 | 0.0, 6 | 0.14906292729135534, 7 | 0.334622858749277 8 | ], 9 | "params": [ 10 | 2.5716142640459654e-05, 11 | 1.0, 12 | 0.3230374361784763, 13 | 2.1319726733259139 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedBetaAnalysis_usa_gdp_1_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3691.3279732097094, 3 | "errors": [ 4 | 0.0021419872826501578, 5 | 0.0, 6 | 2.9465777427143767, 7 | 0.201374456344394 8 | ], 9 | "params": [ 10 | 0.04417647623747186, 11 | 1.0, 12 | 0.03984473604471871, 13 | 2.080800427651319 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedBetaAnalysis_usa_gdp_2_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3691.3279732100154, 3 | "errors": [ 4 | 0.001932106006984638, 5 | 0.0, 6 | 0.13646285261202337, 7 | 0.1758201294884545 8 | ], 9 | "params": [ 10 | 0.04417644463297368, 11 | 1.0, 12 | 0.03984439749291087, 13 | 2.080801067651487 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedBetaAnalysis_usa_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3691.3279732094525, 3 | "errors": [ 4 | 0.0018155145616716702, 5 | 0.0, 6 | 0.10711562678514744, 7 | 0.15866238029043117 8 | ], 9 | "params": [ 10 | 0.044176462185204476, 11 | 1.0, 12 | 0.039844273598686739, 13 | 2.0808015047582247 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedBetaAnalysis_usa_miles_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3474.8088690389113, 3 | "errors": [ 4 | 0.00031298318980590225, 5 | 0.0, 6 | 0.21284931121591419, 7 | 0.1512733407269285 8 | ], 9 | "params": [ 10 | 0.0070920163458057786, 11 | 1.0, 12 | 0.13563650424178461, 13 | 2.072609802103643 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedBetaAnalysis_usa_miles_8_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3474.8088690395934, 3 | "errors": [ 4 | 0.00036031536178438077, 5 | 0.0, 6 | 0.17661915157272134, 7 | 0.1407881476236681 8 | ], 9 | "params": [ 10 | 0.007092009656284771, 11 | 1.0, 12 | 0.1356369082507747, 13 | 2.0726092679955594 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDAnalysis_covid19_brazil_2_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 43846.568781466936, 3 | "errors": [ 4 | 0.012176425530903298, 5 | 0.011754198749476806, 6 | 0.02692158641794988, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.11052092821491939, 11 | 0.9919601968023238, 12 | 0.3544243968993075, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDAnalysis_eurostat_cinema_attendance_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3138.3694812207723, 3 | "errors": [ 4 | 0.10428300938039342, 5 | 0.19352891896038613, 6 | 7.0463181199113327, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.016748770105052685, 11 | 1.4599552062436481, 12 | 8.0083980434693149, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDAnalysis_eurostat_cinema_seats_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3682.824287054199, 3 | "errors": [ 4 | 0.028066993721593065, 5 | 0.088941467789081963, 6 | 0.20994853085196871, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.020178929653342659, 11 | 0.99871042912103214, 12 | 0.75245362409753014, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDAnalysis_eurostat_libraries_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 2073.5146957689412, 3 | "errors": [ 4 | 0.001507313902241856, 5 | 0.10381291903242265, 6 | 0.22904512285652937, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.00093542831248405022, 11 | 0.79754566034971308, 12 | 0.97644022417734888, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDAnalysis_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 5807.264077000772, 3 | "errors": [ 4 | 0.018560385693318179, 5 | 0.11799683452936267, 6 | 1.0741651852590388, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.0083714676586825673, 11 | 1.4235004138698515, 12 | 2.9667730494542122, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDAnalysis_eurostat_theaters_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 814.3091206755779, 3 | "errors": [ 4 | 8.9057390174945776e-05, 5 | 0.089669169158555634, 6 | 0.11628012118987997, 7 | 0.0 8 | ], 9 | "params": [ 10 | 6.2830733437470432e-05, 11 | 0.9107024652171466, 12 | 0.54486912912301855, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDAnalysis_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3029.6873564753741, 3 | "errors": [ 4 | 0.0058590925469678866, 5 | 0.059304529268729707, 6 | 0.045703144168240915, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.0056729202238301009, 11 | 1.1236861120894561, 12 | 0.1757808536262756, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDAnalysis_ocde_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1371.5522450110047, 3 | "errors": [ 4 | 0.00013465601383488734, 5 | 0.26867084451544782, 6 | 8.5933947750754598, 7 | 0.0 8 | ], 9 | "params": [ 10 | 4.6924551249827029e-06, 11 | 1.285235903171096, 12 | 13.680388161663602, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDAnalysis_uk_income_1_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1826.925841893288, 3 | "errors": [ 4 | 688.587854002876, 5 | 0.8600549254967809, 6 | 2.5450471786296163, 7 | 0.0 8 | ], 9 | "params": [ 10 | 2.735468892661463, 11 | 1.399361425376171, 12 | 1.3046183079874174, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDAnalysis_uk_income_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1693.6104370746, 3 | "errors": [ 4 | 165.91066259834901, 5 | 0.043304550739600378, 6 | 0.0071250195438762425, 7 | 0.0 8 | ], 9 | "params": [ 10 | 311.61824766307279, 11 | 0.97088810460776442, 12 | 0.027450452752956322, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDAnalysis_uk_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 548.22783603500204, 3 | "errors": [ 4 | 0.0037102379763241477, 5 | 0.11715696640516292, 6 | 0.23381768719429152, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.0012243936461284156, 11 | 0.99040647225372502, 12 | 0.48089336461259446, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDAnalysis_uk_train_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 204.22588247185598, 3 | "errors": [ 4 | 8.9108252293449032e-05, 5 | 0.13036583478738203, 6 | 0.12204952854102435, 7 | 0.0 8 | ], 9 | "params": [ 10 | 1.6953073146500032e-05, 11 | 1.0351129760680198, 12 | 0.39034587311070934, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDAnalysis_usa_gdp_1_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3655.4004425995954, 3 | "errors": [ 4 | 0.6970916866618004, 5 | 0.1476714895196766, 6 | 0.192881174847168, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.010624443118619846, 11 | 1.112762484947126, 12 | 0.07154201048817685, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDAnalysis_usa_gdp_2_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3655.400442673868, 3 | "errors": [ 4 | 0.03579635200098983, 5 | 0.06125202206921292, 6 | 0.02866902046186189, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.010624039725817155, 11 | 1.1127655008015638, 12 | 0.0715409648148752, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDAnalysis_usa_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3655.4004425363128, 3 | "errors": [ 4 | 0.003763521983893613, 5 | 0.025228842015003399, 6 | 0.014053836578449547, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.010624972027430263, 11 | 1.1127586004882366, 12 | 0.071541180001306132, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDAnalysis_usa_miles_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3440.7802115054692, 3 | "errors": [ 4 | 0.017561507720980089, 5 | 0.032527555443242928, 6 | 0.056798917113399898, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.043584155651648707, 11 | 0.84666706478405607, 12 | 0.1901743850669014, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDAnalysis_usa_miles_8_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3440.7802115057993, 3 | "errors": [ 4 | 0.015778181019534012, 5 | 0.028641550591788325, 6 | 0.05483324691681817, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.043583925220575824, 11 | 0.8466674769713392, 12 | 0.19017433619577162, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedB_eurostat_cinema_attendance_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3145.813810914741, 3 | "params": [ 4 | 4.593335069771621, 5 | 1.0, 6 | 9.4997156955621, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedB_eurostat_cinema_seats_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3682.8246482510103, 3 | "params": [ 4 | 0.01987216956194885, 5 | 1.0, 6 | 0.752455162097411, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedB_eurostat_libraries_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 2083.8625551370515, 3 | "params": [ 4 | 8.35889228913304e-05, 5 | 1.0, 6 | 1.0245003567660758, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedB_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 5824.836997099301, 3 | "params": [ 4 | 1.3938210774231548, 5 | 1.0, 6 | 3.4447697267903052, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedB_eurostat_theaters_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 816.5835617421108, 3 | "params": [ 4 | 2.1557163951362585e-05, 5 | 1.0, 6 | 0.5527659152954479, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedB_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3037.606030143137, 3 | "params": [ 4 | 0.03231043143967564, 5 | 1.0, 6 | 0.18712088235908153, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedB_ocde_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1373.5957626747631, 3 | "params": [ 4 | 0.0002608941876321983, 5 | 1.0, 6 | 14.443260135598962, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedB_uk_income_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1695.0464592152862, 3 | "params": [ 4 | 220.20248467220716, 5 | 1.0, 6 | 0.028261494325455612, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedB_uk_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 548.238567396842, 3 | "params": [ 4 | 0.001091716792426703, 5 | 1.0, 6 | 0.4810252685072571, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedB_uk_train_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 204.39360012614557, 3 | "params": [ 4 | 2.5822032235853016e-05, 5 | 1.0, 6 | 0.39201403282695946, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedB_usa_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3691.9947518630725, 3 | "params": [ 4 | 0.04462746932741702, 5 | 1.0, 6 | 0.0873371154329182, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedB_usa_miles_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3475.631606936722, 3 | "params": [ 4 | 0.007006890131209426, 5 | 1.0, 6 | 0.22464528987255009, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedBetaAnalysis_eurostat_cinema_attendance_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3145.8138109147458, 3 | "errors": [ 4 | 0.87973962398109706, 5 | 0.0, 6 | 6.3867884469933847, 7 | 0.0 8 | ], 9 | "params": [ 10 | 4.5933318562182102, 11 | 1.0, 12 | 9.4997034128524849, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedBetaAnalysis_eurostat_cinema_seats_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3682.8246482510094, 3 | "errors": [ 4 | 0.0011433289709802598, 5 | 0.0, 6 | 0.23256063219758782, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.019872169252671344, 11 | 1.0, 12 | 0.75245509534150234, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedBetaAnalysis_eurostat_libraries_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 2083.8625551396431, 3 | "errors": [ 4 | 4.8341462636820392e-06, 5 | 0.0, 6 | 0.32440192264018047, 7 | 0.0 8 | ], 9 | "params": [ 10 | 8.3588990377635872e-05, 11 | 1.0, 12 | 1.0245070814642949, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedBetaAnalysis_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 5824.8369970993008, 3 | "errors": [ 4 | 0.19723635480803381, 5 | 0.0, 6 | 1.1133122209006643, 7 | 0.0 8 | ], 9 | "params": [ 10 | 1.3938209196446081, 11 | 1.0, 12 | 3.4447695261732942, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedBetaAnalysis_eurostat_theaters_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 816.58356177536359, 3 | "errors": [ 4 | 1.6798571732388736e-06, 5 | 0.0, 6 | 0.10825978035645795, 7 | 0.0 8 | ], 9 | "params": [ 10 | 2.1557026594451403e-05, 11 | 1.0, 12 | 0.55275226101051578, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedBetaAnalysis_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3037.6060301431389, 3 | "errors": [ 4 | 0.0011119107399858014, 5 | 0.0, 6 | 0.050755222440375974, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.032310431477025787, 11 | 1.0, 12 | 0.18712091476389767, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedBetaAnalysis_ocde_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1373.5957626751069, 3 | "errors": [ 4 | 5.0947020252054156e-05, 5 | 0.0, 6 | 7.4332750053844583, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.00026089325538366056, 11 | 1.0, 12 | 14.443133568155368, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedBetaAnalysis_uk_income_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1695.0464592153166, 3 | "errors": [ 4 | 7.1802495274166009, 5 | 0.0, 6 | 0.00754076289212778, 7 | 0.0 8 | ], 9 | "params": [ 10 | 220.20245505720391, 11 | 1.0, 12 | 0.0282614988449277, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedBetaAnalysis_uk_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 548.23856739683038, 3 | "errors": [ 4 | 0.00019794882523841548, 5 | 0.0, 6 | 0.20359151330730627, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.001091716589504617, 11 | 1.0, 12 | 0.48102508693493384, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedBetaAnalysis_uk_train_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 204.39360011003203, 3 | "errors": [ 4 | 3.0400537395178674e-06, 5 | 0.0, 6 | 0.11384452753586469, 7 | 0.0 8 | ], 9 | "params": [ 10 | 2.5822240016277413e-05, 11 | 1.0, 12 | 0.3920110639022566, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedBetaAnalysis_usa_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3691.9947518630729, 3 | "errors": [ 4 | 0.0015028511438690167, 5 | 0.0, 6 | 0.019151604614578467, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.044627469042653793, 11 | 1.0, 12 | 0.087337120111595556, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedDFixedBetaAnalysis_usa_miles_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3475.6316069367331, 3 | "errors": [ 4 | 0.00031642664724062706, 5 | 0.0, 6 | 0.052789237740387462, 7 | 0.0 8 | ], 9 | "params": [ 10 | 0.0070068913746932741, 11 | 1.0, 12 | 0.22464540628157009, 13 | 2.0 14 | ] 15 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedD_eurostat_cinema_attendance_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3138.3694812207905, 3 | "params": [ 4 | 0.016748656956019008, 5 | 1.4599557797484572, 6 | 8.008391475865283, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedD_eurostat_cinema_seats_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3682.82428705412, 3 | "params": [ 4 | 0.020178539085699686, 5 | 0.9987121150125808, 6 | 0.7524532056740922, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedD_eurostat_libraries_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 2073.514695751343, 3 | "params": [ 4 | 0.0009354858245089164, 5 | 0.7975410010242096, 6 | 0.9764306800693257, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedD_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 5807.26407700165, 3 | "params": [ 4 | 0.008371454850813904, 5 | 1.423500755671305, 6 | 2.96678293281727, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedD_eurostat_theaters_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 814.3091174431929, 3 | "params": [ 4 | 6.278503463805428e-05, 5 | 0.9107675507125462, 6 | 0.5450305548286279, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedD_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3029.687356476214, 3 | "params": [ 4 | 0.0056727247850427535, 5 | 1.123688673386274, 6 | 0.1757799422173104, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedD_ocde_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1371.5522389395442, 3 | "params": [ 4 | 4.7325931227476985e-06, 5 | 1.2846466596012087, 6 | 13.687234939271661, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedD_uk_income_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1693.610437075118, 3 | "params": [ 4 | 311.61727198634355, 5 | 0.9708884083499374, 6 | 0.02745047421037352, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedD_uk_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 548.2278360382389, 3 | "params": [ 4 | 0.0012243508206941777, 5 | 0.990408701797444, 6 | 0.480891511978439, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedD_uk_train_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 204.22587851777016, 3 | "params": [ 4 | 1.6958647842706427e-05, 5 | 1.0350707157726, 6 | 0.39037659172174155, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedD_usa_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3655.4004425349813, 3 | "params": [ 4 | 0.010624904235749551, 5 | 1.112759107004664, 6 | 0.07154091080924724, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFixedD_usa_miles_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3440.7802115054246, 3 | "params": [ 4 | 0.043584175681404054, 5 | 0.8466669929123338, 6 | 0.19017427051956165, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeDFixedB_eurostat_cinema_attendance_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3132.6528381831204, 3 | "params": [ 4 | 4.292370514073994, 5 | 1.0, 6 | 4163064.515265013, 7 | 1.0229502629930445 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeDFixedB_eurostat_cinema_seats_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3658.9061045666135, 3 | "params": [ 4 | 0.018423913676338707, 5 | 1.0, 6 | 247.50668695357763, 7 | 1.240578759444788 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeDFixedB_eurostat_libraries_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 2080.2410267461837, 3 | "params": [ 4 | 8.479762080334158e-05, 5 | 1.0, 6 | 0.6093875620012799, 7 | 2.199521269657568 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeDFixedB_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 5818.138050627425, 3 | "params": [ 4 | 1.5200898159940979, 5 | 1.0, 6 | 1298.0210868956128, 7 | 1.5255758076260124 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeDFixedB_eurostat_theaters_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 807.4198013746332, 3 | "params": [ 4 | 2.182867717219006e-05, 5 | 1.0, 6 | 0.2846893674295438, 7 | 2.496866254474633 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeDFixedB_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3036.38302461533, 3 | "params": [ 4 | 0.032749301292502406, 5 | 1.0, 6 | 1.3161880167755, 7 | 1.8165331626824992 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeDFixedB_ocde_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1371.1920231334498, 3 | "params": [ 4 | 0.0002606301550684813, 5 | 1.0, 6 | 199.22018474156135, 7 | 1.5390616557082415 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeDFixedB_uk_income_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1695.028976903102, 3 | "params": [ 4 | 220.05800717398867, 5 | 1.0, 6 | 0.04282106979393613, 7 | 1.975970925245989 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeDFixedB_uk_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 546.9260581323233, 3 | "params": [ 4 | 0.0010753992985479042, 5 | 1.0, 6 | 2.1021928649532775, 7 | 1.7038896731738173 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeDFixedB_uk_train_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 204.1698064662766, 3 | "params": [ 4 | 2.5716431566168597e-05, 5 | 1.0, 6 | 0.323061718342721, 7 | 2.131952282764211 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeDFixedB_usa_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3691.3279732094684, 3 | "params": [ 4 | 0.044176459149547716, 5 | 1.0, 6 | 0.03984419141833969, 7 | 2.0808017098469307 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeDFixedB_usa_miles_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3474.8088690389286, 3 | "params": [ 4 | 0.007092014634644935, 5 | 1.0, 6 | 0.13563643714948959, 7 | 2.0726098782527553 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeD_eurostat_cinema_attendance_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3132.65320221469, 3 | "params": [ 4 | 4.536242949028317, 5 | 0.9955273595966667, 6 | 3835766.1925911317, 7 | 1.0288449106529625 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeD_eurostat_cinema_seats_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3653.5042432231135, 3 | "params": [ 4 | 0.0646619921890356, 5 | 0.8989915867461002, 6 | 1255.7061463811924, 7 | 1.0452598106726778 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeD_eurostat_libraries_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 2073.1758843025254, 3 | "params": [ 4 | 0.0007689522937907845, 5 | 0.813878789839853, 6 | 0.7767391981058659, 7 | 2.0879348869387453 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeD_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 5805.334580872599, 3 | "params": [ 4 | 0.0198794282837845, 5 | 1.3509620207596793, 6 | 40.21952269103336, 7 | 1.7859014464642429 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeD_eurostat_theaters_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 805.9872656425131, 3 | "params": [ 4 | 5.6099233547532455e-05, 5 | 0.9195539959624359, 6 | 0.2758650521588987, 7 | 2.5066950938296393 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeD_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3029.4163676785492, 3 | "params": [ 4 | 0.006548535719767662, 5 | 1.1134599025838001, 6 | 0.39873901064287987, 7 | 1.9224739626276337 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeD_ocde_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1370.9525262266027, 3 | "params": [ 4 | 4.4526731113839175e-05, 5 | 1.1243031579101959, 6 | 74.18680861197589, 7 | 1.7029740839112582 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeD_uk_income_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1693.6093448690551, 3 | "params": [ 4 | 312.4679462604469, 5 | 0.9706598837078926, 6 | 0.02483030681980418, 7 | 2.0057854244934137 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeD_uk_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 546.7126323585567, 3 | "params": [ 4 | 0.0016327465136647742, 5 | 0.9660364396908253, 6 | 2.4682210182753197, 7 | 1.674588727439776 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeD_uk_train_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 204.0756314724167, 3 | "params": [ 4 | 1.8286560114929807e-05, 5 | 1.0287180117104493, 6 | 0.33196939001302567, 7 | 2.1128308844940316 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeD_usa_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3654.0678712467015, 3 | "params": [ 4 | 0.010592230426006113, 5 | 1.1129823020148917, 6 | 0.19261254190504756, 7 | 1.8954866101867174 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_LogNormalFreeD_usa_miles_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3425.518623731202, 3 | "params": [ 4 | 0.06063861489305692, 5 | 0.8192632108925467, 6 | 4.457946463002677, 7 | 1.542539210950391 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFixedD_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3074.691018164329, 3 | "params": [ 4 | 0.00845413218858843, 5 | 1.0934019375453534, 6 | 7785.245884999617, 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeDFixedB_eurostat_cinema_attendance_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3128.6201820421106, 3 | "params": [ 4 | 2.7133662408514767, 5 | 1.0, 6 | 35.14557642759212, 7 | 1.6810215627039053 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeDFixedB_eurostat_cinema_seats_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3673.194243202345, 3 | "params": [ 4 | 0.01754947265179602, 5 | 1.0, 6 | 253.791707490264, 7 | 1.174028408618239 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeDFixedB_eurostat_libraries_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 2077.7701249454813, 3 | "params": [ 4 | 6.982147361666902e-05, 5 | 1.0, 6 | 2.2544914601142683, 7 | 1.368354640474452 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeDFixedB_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 6352.398182936402, 3 | "params": [ 4 | 1.3940004302978337, 5 | 1.0, 6 | 3.6317542791326756, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeDFixedB_eurostat_theaters_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1007.9488213591833, 3 | "params": [ 4 | 2.1873412331570762e-05, 5 | 1.0, 6 | 0.7200460057643212, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeDFixedB_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3006.287701428553, 3 | "params": [ 4 | 0.031913037937662134, 5 | 1.0, 6 | 0.11794448718599532, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeDFixedB_ocde_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1505.8851548845923, 3 | "params": [ 4 | 0.00015330424296164675, 5 | 1.0, 6 | 5.491919046631304, 7 | 1.7782577275977314 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeDFixedB_uk_income_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1700.1850955500104, 3 | "params": [ 4 | 219.84730117591303, 5 | 1.0, 6 | 0.10365466688009221, 7 | 1.9287295789429149 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeDFixedB_uk_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 609.2687267246368, 3 | "params": [ 4 | 0.0011044236620499537, 5 | 1.0, 6 | 6.83345219792331, 7 | 1.6195452680059301 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeDFixedB_uk_train_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 219.48589181699174, 3 | "params": [ 4 | 2.56630700049451e-05, 5 | 1.0, 6 | 0.3283811614843569, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeDFixedB_usa_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3745.151066581458, 3 | "params": [ 4 | 0.04469582621320457, 5 | 1.0, 6 | 0.10147988485979213, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeDFixedB_usa_miles_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3606.1617017826684, 3 | "params": [ 4 | 0.005740192727125157, 5 | 1.0, 6 | 37.38973887452449, 7 | 1.3502760132783096 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeD_eurostat_cinema_attendance_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3124.4963310463345, 3 | "params": [ 4 | 0.51285863335007309, 5 | 1.1347675524244263, 6 | 257.27359173394132, 7 | 1.5305721059151345 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeD_eurostat_cinema_seats_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3668.4228440837001, 3 | "params": [ 4 | 0.050104899539407582, 5 | 0.91621132187618282, 6 | 87.88678151714555, 7 | 1.2975384658777007 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeD_eurostat_libraries_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 2050.2160829958202, 3 | "params": [ 4 | 0.0010608255492350568, 5 | 0.77964104791111122, 6 | 0.84633439022669632, 7 | 1.6803240327774407 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeD_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 6343.6165517605159, 3 | "params": [ 4 | 0.013132785390555428, 5 | 1.3856224142239695, 6 | 1443.1643328855985, 7 | 1.5165379184601735 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeD_eurostat_theaters_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 996.95169723589743, 3 | "params": [ 4 | 3.9898648399609976e-06, 5 | 1.1422671462918044, 6 | 0.6729570656023065, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeD_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 2991.8172106700194, 3 | "params": [ 4 | 0.0054686245904560981, 5 | 1.1254309363942772, 6 | 0.10715092859243554, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeD_ocde_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1504.6889229747583, 3 | "params": [ 4 | 2.3386026691439335e-05, 5 | 1.1323999600368666, 6 | 17.357695207641381, 7 | 1.5633784133349964 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeD_uk_income_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1698.9214313889029, 3 | "params": [ 4 | 304.72881509340186, 5 | 0.97278669523723793, 6 | 0.029292302412910663, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeD_uk_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 609.12765035962354, 3 | "params": [ 4 | 0.0018835263962094302, 5 | 0.95702565174546128, 6 | 4.1755125529014379, 7 | 1.7079974968873011 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeD_uk_train_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 218.82770324631295, 3 | "params": [ 4 | 1.4762102702233565e-05, 5 | 1.0461292716754478, 6 | 0.32399317674875111, 7 | 2.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeD_usa_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3709.9782507318678, 3 | "params": [ 4 | 0.010205965101081104, 5 | 1.1159595138752181, 6 | 0.86057933628915984, 7 | 1.758514747752205 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_NormalFreeD_usa_miles_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3519.8699243446517, 3 | "params": [ 4 | 0.06486745348716709, 5 | 0.81380034245756694, 6 | 36.536702842263935, 7 | 1.2641149788992831 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationAnalysis_covid19_brazil_2_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 152546602.51639697, 3 | "errors": [ 4 | 0.031075411216677645 5 | ], 6 | "params": [ 7 | 0.9879323069911359 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationAnalysis_eurostat_cinema_attendance_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 829480184.72830546, 3 | "errors": [ 4 | 0.088327082535509818 5 | ], 6 | "params": [ 7 | 1.0603904787596674 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationAnalysis_eurostat_cinema_seats_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 8663979.5774623118, 3 | "errors": [ 4 | 0.075533452875518811 5 | ], 6 | "params": [ 7 | 0.93361643170209185 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationAnalysis_eurostat_libraries_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 55001.528853427546, 3 | "errors": [ 4 | 0.11779839524911297 5 | ], 6 | "params": [ 7 | 0.76402913088624436 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationAnalysis_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1094242295.2391353, 3 | "errors": [ 4 | 0.20702369233688514 5 | ], 6 | "params": [ 7 | 1.4581837232164545 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationAnalysis_eurostat_theaters_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 12287.317048919127, 3 | "errors": [ 4 | 0.16370617850756553 5 | ], 6 | "params": [ 7 | 1.0857848124508784 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationAnalysis_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 93001998.973817438, 3 | "errors": [ 4 | 0.072512100683041952 5 | ], 6 | "params": [ 7 | 1.0508097763304787 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationAnalysis_ocde_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 330234.94478291192, 3 | "errors": [ 4 | 0.17130749013490087 5 | ], 6 | "params": [ 7 | 1.0849866925081313 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationAnalysis_uk_income_16_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 25576540092.75958, 3 | "errors": [ 4 | 0.12614461566838264 5 | ], 6 | "params": [ 7 | 1.0588569626198117 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationAnalysis_uk_income_1_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 25576540092.759575, 3 | "errors": [ 4 | 0.1396789835960841 5 | ], 6 | "params": [ 7 | 1.0588569627095519 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationAnalysis_uk_income_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 25576540092.759571, 3 | "errors": [ 4 | 0.14501660320957521 5 | ], 6 | "params": [ 7 | 1.0588569602033169 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationAnalysis_uk_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 119222.00297788193, 3 | "errors": [ 4 | 0.25368851660614072 5 | ], 6 | "params": [ 7 | 1.0439199408911835 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationAnalysis_uk_train_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3340.1172512884496, 3 | "errors": [ 4 | 0.15845708845936549 5 | ], 6 | "params": [ 7 | 1.1878666736419903 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationAnalysis_usa_gdp_1_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 70846201.94868022, 3 | "errors": [ 4 | 0.02426091436351281 5 | ], 6 | "params": [ 7 | 1.121031342805009 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationAnalysis_usa_gdp_2_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 70846201.94868007, 3 | "errors": [ 4 | 0.02077986617381453 5 | ], 6 | "params": [ 7 | 1.1210314399746837 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationAnalysis_usa_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 70846201.948680058, 3 | "errors": [ 4 | 0.023798281140764582 5 | ], 6 | "params": [ 7 | 1.1210314431617572 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationAnalysis_usa_miles_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 5075738.0029744888, 3 | "errors": [ 4 | 0.037054248821352602 5 | ], 6 | "params": [ 7 | 0.80712127162897085 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationAnalysis_usa_miles_8_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 5075738.00297449, 3 | "errors": [ 4 | 0.0377747720448735 5 | ], 6 | "params": [ 7 | 0.8071212607697648 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationFixedGammaAnalysis_covid19_brazil_2_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 152553367.7258924, 3 | "errors": [ 4 | 0.0 5 | ], 6 | "params": [ 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationFixedGammaAnalysis_eurostat_cinema_attendance_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 829877777.6278777, 3 | "errors": [ 4 | 0.0 5 | ], 6 | "params": [ 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationFixedGammaAnalysis_eurostat_cinema_seats_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 8668061.70427658, 3 | "errors": [ 4 | 0.0 5 | ], 6 | "params": [ 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationFixedGammaAnalysis_eurostat_libraries_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 55244.756343953326, 3 | "errors": [ 4 | 0.0 5 | ], 6 | "params": [ 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationFixedGammaAnalysis_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1124298271.7569695, 3 | "errors": [ 4 | 0.0 5 | ], 6 | "params": [ 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationFixedGammaAnalysis_eurostat_theaters_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 12297.795212991383, 3 | "errors": [ 4 | 0.0 5 | ], 6 | "params": [ 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationFixedGammaAnalysis_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 93040879.15925315, 3 | "errors": [ 4 | 0.0 5 | ], 6 | "params": [ 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationFixedGammaAnalysis_ocde_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 330658.1882527682, 3 | "errors": [ 4 | 0.0 5 | ], 6 | "params": [ 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationFixedGammaAnalysis_uk_income_16_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 25611318318.340374, 3 | "errors": [ 4 | 0.0 5 | ], 6 | "params": [ 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationFixedGammaAnalysis_uk_income_1_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 25611318318.340374, 3 | "errors": [ 4 | 0.0 5 | ], 6 | "params": [ 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationFixedGammaAnalysis_uk_income_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 25611318318.340374, 3 | "errors": [ 4 | 0.0 5 | ], 6 | "params": [ 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationFixedGammaAnalysis_uk_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 119311.87838507567, 3 | "errors": [ 4 | 0.0 5 | ], 6 | "params": [ 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationFixedGammaAnalysis_uk_train_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 3389.7956456121874, 3 | "errors": [ 4 | 0.0 5 | ], 6 | "params": [ 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationFixedGammaAnalysis_usa_gdp_1_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 71068060.10573396, 3 | "errors": [ 4 | 0.0 5 | ], 6 | "params": [ 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationFixedGammaAnalysis_usa_gdp_2_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 71068060.10573396, 3 | "errors": [ 4 | 0.0 5 | ], 6 | "params": [ 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationFixedGammaAnalysis_usa_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 71068060.10573396, 3 | "errors": [ 4 | 0.0 5 | ], 6 | "params": [ 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationFixedGammaAnalysis_usa_miles_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 5123383.344442837, 3 | "errors": [ 4 | 0.0 5 | ], 6 | "params": [ 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_PopulationFixedGammaAnalysis_usa_miles_8_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 5123383.344442837, 3 | "errors": [ 4 | 0.0 5 | ], 6 | "params": [ 7 | 1.0 8 | ] 9 | } -------------------------------------------------------------------------------- /notebooks/_results/mle_Population_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "-log_likelihood": 1094242295.2391353, 3 | "params": [ 4 | 1.4581837208742043 5 | ] 6 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationAnalysis_covid19_brazil_2_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationAnalysis_eurostat_cinema_attendance_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationAnalysis_eurostat_cinema_seats_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationAnalysis_eurostat_libraries_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationAnalysis_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationAnalysis_eurostat_theaters_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationAnalysis_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationAnalysis_ocde_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationAnalysis_uk_income_16_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationAnalysis_uk_income_1_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationAnalysis_uk_income_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationAnalysis_uk_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationAnalysis_uk_train_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationAnalysis_usa_gdp_1_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationAnalysis_usa_gdp_2_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationAnalysis_usa_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationAnalysis_usa_miles_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationAnalysis_usa_miles_8_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationFixedGammaAnalysis_covid19_brazil_2_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationFixedGammaAnalysis_eurostat_cinema_attendance_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationFixedGammaAnalysis_eurostat_cinema_seats_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationFixedGammaAnalysis_eurostat_libraries_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationFixedGammaAnalysis_eurostat_museum_visitors_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationFixedGammaAnalysis_eurostat_theaters_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationFixedGammaAnalysis_ocde_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationFixedGammaAnalysis_ocde_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationFixedGammaAnalysis_uk_income_16_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationFixedGammaAnalysis_uk_income_1_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationFixedGammaAnalysis_uk_income_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationFixedGammaAnalysis_uk_patents_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationFixedGammaAnalysis_uk_train_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationFixedGammaAnalysis_usa_gdp_1_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationFixedGammaAnalysis_usa_gdp_2_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationFixedGammaAnalysis_usa_gdp_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationFixedGammaAnalysis_usa_miles_512_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /notebooks/_results/pvalue_PopulationFixedGammaAnalysis_usa_miles_8_100.json: -------------------------------------------------------------------------------- 1 | { 2 | "p_value": 0.0 3 | } -------------------------------------------------------------------------------- /src/__pycache__/analysis.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/src/__pycache__/analysis.cpython-36.pyc -------------------------------------------------------------------------------- /src/__pycache__/analysis.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/src/__pycache__/analysis.cpython-38.pyc -------------------------------------------------------------------------------- /src/__pycache__/best_parameters.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/src/__pycache__/best_parameters.cpython-36.pyc -------------------------------------------------------------------------------- /src/__pycache__/best_parameters.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/src/__pycache__/best_parameters.cpython-38.pyc -------------------------------------------------------------------------------- /src/__pycache__/pvalue_population.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/src/__pycache__/pvalue_population.cpython-36.pyc -------------------------------------------------------------------------------- /src/__pycache__/pvalue_population.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edugalt/scaling/ccdaac18b0d1ce8a09a239353a32264f79d28ead/src/__pycache__/pvalue_population.cpython-38.pyc -------------------------------------------------------------------------------- /src/analysis_run.py: -------------------------------------------------------------------------------- 1 | import os 2 | 3 | import numpy as np 4 | 5 | from analysis import DATABASES, MODELS 6 | 7 | # force all warnings to be errors 8 | np.seterr(all='raise') 9 | 10 | # read from env. 11 | required_successes = os.getenv('REQUIRED_SUCCESSES') 12 | database = os.getenv('DATABASE') 13 | model = os.getenv('MODEL') 14 | 15 | if required_successes is None or database is None or model is None: 16 | available_databases = '\n\t'.join(DATABASES.keys()) 17 | available_models = '\n\t'.join(MODELS.keys()) 18 | message = 'Available databases:\n\t%s\nAvailable models:\n\t%s' % \ 19 | (available_databases, available_models) 20 | 21 | print(message) 22 | print("INFO: to run this file, you must set environment variables MODEL, REQUIRED_SUCCESSES, and DATABASE. " 23 | "For example,\n" 24 | "\tDATABASE=brazil_aids_2010 MODEL=LogNormalAnalysis REQUIRED_SUCCESSES=8 python -m analysis_run") 25 | print("\tAvailable models and analysis are listed above.") 26 | exit(1) 27 | 28 | required_successes = int(required_successes) 29 | 30 | Model = MODELS[model] 31 | if database not in DATABASES: 32 | raise IndexError('Database "%s" is invalid.' % database) 33 | 34 | print('Running analysis for model "%s" on database "%s" for "%d" successes.' % 35 | (database, model, required_successes)) 36 | 37 | # run the analysis 38 | Model(database, required_successes=required_successes) 39 | -------------------------------------------------------------------------------- /src/pvalue_population.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | from best_parameters import minimize, PopulationModel 3 | 4 | 5 | # best_fit = population_likelihood_best_fit 6 | 7 | 8 | def chi2(y0, y1): 9 | return np.sum(np.power(y0 - y1, 2.0) / y1) 10 | 11 | 12 | def chi2_gamma(x, y, gamma): 13 | y1 = np.power(x, gamma) / np.sum(np.power(x, gamma)) * np.sum(y) 14 | return chi2(y, y1) 15 | 16 | 17 | def sample_pop_model(fx, n): 18 | sample = np.random.multinomial(n, fx) 19 | return sample 20 | 21 | 22 | def pvalue_pop(x, y, params, bounds, samples=200): 23 | gamma0 = params[0] 24 | chi20 = chi2_gamma(x, y, gamma0) 25 | n = int(np.sum(y)) # number of tokens 26 | chi2s, gammas = [], [] 27 | fx = np.power(x, gamma0) 28 | fx = fx / np.sum(fx) 29 | 30 | model = PopulationModel(bounds) 31 | 32 | for i in range(samples): 33 | sample = sample_pop_model(fx, n) 34 | gamma = minimize(model, x, sample, disp=False) 35 | gammas.append(gamma[0][0]) 36 | chi21 = chi2_gamma(x, sample, gamma[0][0]) 37 | chi2s.append(chi21) 38 | chi2s = np.array(chi2s) 39 | mask = (chi2s > chi20) 40 | p_value = len(chi2s[mask]) / float(len(chi2s)) 41 | return p_value 42 | --------------------------------------------------------------------------------