├── header.html ├── .gitattributes ├── .gitignore ├── landings.RData ├── images ├── aquaduct.jpg ├── fish-forecast.jpg ├── GitHub_pages_1.png ├── GitHub_pages_2.png ├── aquaduct-sepia.jpg ├── RStudio-screenshot.png └── tools-logo-transparent.png ├── fish forecast syllabus.pdf ├── README.md ├── data_files └── figure-html │ └── load_data-1.png ├── site_libs ├── bootstrap-3.3.5 │ ├── css │ │ └── fonts │ │ │ ├── Lato.ttf │ │ │ ├── Raleway.ttf │ │ │ ├── Roboto.ttf │ │ │ ├── Ubuntu.ttf │ │ │ ├── LatoBold.ttf │ │ │ ├── NewsCycle.ttf │ │ │ ├── OpenSans.ttf │ │ │ ├── LatoItalic.ttf │ │ │ ├── OpenSansBold.ttf │ │ │ ├── RalewayBold.ttf │ │ │ ├── RobotoBold.ttf │ │ │ ├── RobotoLight.ttf │ │ │ ├── RobotoMedium.ttf │ │ │ ├── NewsCycleBold.ttf │ │ │ ├── OpenSansItalic.ttf │ │ │ ├── OpenSansLight.ttf │ │ │ ├── SourceSansPro.ttf │ │ │ ├── SourceSansProBold.ttf │ │ │ ├── OpenSansBoldItalic.ttf │ │ │ ├── OpenSansLightItalic.ttf │ │ │ ├── SourceSansProItalic.ttf │ │ │ └── SourceSansProLight.ttf │ ├── fonts │ │ ├── glyphicons-halflings-regular.eot │ │ ├── glyphicons-halflings-regular.ttf │ │ ├── glyphicons-halflings-regular.woff │ │ └── glyphicons-halflings-regular.woff2 │ ├── js │ │ └── npm.js │ └── shim │ │ ├── html5shiv.min.js │ │ └── respond.min.js ├── font-awesome-5.0.13 │ ├── fonts │ │ ├── fa-solid-900.ttf │ │ ├── fa-brands-400.ttf │ │ └── fa-regular-400.ttf │ ├── css │ │ └── fa-svg-with-js.css │ └── js │ │ └── fa-v4-shims.min.js ├── font-awesome-5.1.0 │ └── webfonts │ │ ├── fa-solid-900.eot │ │ ├── fa-solid-900.ttf │ │ ├── fa-brands-400.eot │ │ ├── fa-brands-400.ttf │ │ ├── fa-brands-400.woff │ │ ├── fa-brands-400.woff2 │ │ ├── fa-regular-400.eot │ │ ├── fa-regular-400.ttf │ │ ├── fa-regular-400.woff │ │ ├── fa-solid-900.woff │ │ ├── fa-solid-900.woff2 │ │ └── fa-regular-400.woff2 ├── font-awesome-4.5.0 │ └── fonts │ │ └── fontawesome-webfont.ttf ├── jqueryui-1.11.4 │ ├── images │ │ ├── ui-icons_444444_256x240.png │ │ ├── ui-icons_555555_256x240.png │ │ ├── ui-icons_777620_256x240.png │ │ ├── ui-icons_777777_256x240.png │ │ ├── ui-icons_cc0000_256x240.png │ │ └── ui-icons_ffffff_256x240.png │ ├── README │ ├── jquery-ui.structure.min.css │ ├── jquery-ui.theme.min.css │ └── jquery-ui.structure.css ├── highlightjs-9.12.0 │ ├── default.css │ └── textmate.css ├── navigation-1.1 │ ├── sourceembed.js │ ├── codefolding.js │ └── tabsets.js └── tocify-1.9.1 │ └── jquery.tocify.css ├── aboutyou.Rmd ├── contact.Rmd ├── styles.css ├── footer.html ├── _site.yml ├── nextsteps.Rmd ├── data.Rmd ├── index.Rmd ├── syllabus.Rmd ├── notes.Rmd ├── set-up.Rmd ├── README.html ├── contact.html ├── aboutyou.html ├── data.html ├── index.html ├── nextsteps.html ├── notes.html └── syllabus.html /header.html: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /.gitattributes: -------------------------------------------------------------------------------- 1 | # Auto detect text files and perform LF normalization 2 | * text=auto 3 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | .Rproj.user 2 | .Rhistory 3 | .RData 4 | .Ruserdata 5 | *.Rproj 6 | .DS_Store 7 | -------------------------------------------------------------------------------- /landings.RData: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/RVerse-Tutorials/Fish-Forecast-Training-Course/master/landings.RData -------------------------------------------------------------------------------- /images/aquaduct.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/RVerse-Tutorials/Fish-Forecast-Training-Course/master/images/aquaduct.jpg -------------------------------------------------------------------------------- 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/site_libs/bootstrap-3.3.5/fonts/glyphicons-halflings-regular.woff2: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/RVerse-Tutorials/Fish-Forecast-Training-Course/master/site_libs/bootstrap-3.3.5/fonts/glyphicons-halflings-regular.woff2 -------------------------------------------------------------------------------- /aboutyou.Rmd: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Comments and Questions" 3 | output: 4 | html_document: 5 | include: 6 | after_body: footer.html 7 | before_body: header.html 8 | --- 9 | 10 | Post questions and problems here. -------------------------------------------------------------------------------- /site_libs/highlightjs-9.12.0/default.css: -------------------------------------------------------------------------------- 1 | .hljs-literal { 2 | color: #990073; 3 | } 4 | 5 | .hljs-number { 6 | color: #099; 7 | } 8 | 9 | .hljs-comment { 10 | color: #998; 11 | font-style: italic; 12 | } 13 | 14 | .hljs-keyword { 15 | color: #900; 16 | font-weight: bold; 17 | } 18 | 19 | .hljs-string { 20 | color: #d14; 21 | } 22 | -------------------------------------------------------------------------------- /site_libs/highlightjs-9.12.0/textmate.css: -------------------------------------------------------------------------------- 1 | .hljs-literal { 2 | color: rgb(88, 72, 246); 3 | } 4 | 5 | .hljs-number { 6 | color: rgb(0, 0, 205); 7 | } 8 | 9 | .hljs-comment { 10 | color: rgb(76, 136, 107); 11 | } 12 | 13 | .hljs-keyword { 14 | color: rgb(0, 0, 255); 15 | } 16 | 17 | .hljs-string { 18 | color: rgb(3, 106, 7); 19 | } 20 | -------------------------------------------------------------------------------- /site_libs/navigation-1.1/sourceembed.js: -------------------------------------------------------------------------------- 1 | 2 | window.initializeSourceEmbed = function(filename) { 3 | $("#rmd-download-source").click(function() { 4 | var src = $("#rmd-source-code").html(); 5 | var a = document.createElement('a'); 6 | a.href = "data:text/x-r-markdown;base64," + src; 7 | a.download = filename; 8 | document.body.appendChild(a); 9 | a.click(); 10 | document.body.removeChild(a); 11 | }); 12 | }; 13 | -------------------------------------------------------------------------------- /site_libs/jqueryui-1.11.4/README: -------------------------------------------------------------------------------- 1 | This a jQuery UI custom build, downloaded from: 2 | http://jqueryui.com/download/#!version=1.11.4&components=1111111111110111111111111111111111111 3 | 4 | It includes all components except the datepicker, because it conflicts with 5 | bootstrap-datepicker that is packaged with Shiny. 6 | 7 | The copy of jQuery that is bundled with the download, under external/, is not 8 | included because Shiny already has its own copy of jQuery. 9 | -------------------------------------------------------------------------------- /contact.Rmd: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Contact" 3 | output: 4 | html_document: 5 | include: 6 | before_body: header.html 7 | --- 8 | 9 | Eli Holmes 10 | 11 | [National Marine Fisheries Service](https://www.fisheries.noaa.gov/) 12 | 13 | [Northwest Fisheries Science Center](https://www.nwfsc.noaa.gov/) 14 | 15 | 2725 Montlake Blvd East 16 | 17 | Seattle, WA 18 | 19 | eli.holmes@noaa.gov 20 | 21 | https://eeholmes.github.io/ 22 | 23 | [NOAA Staff Page](https://www.nwfsc.noaa.gov/contact/display_staffprofile.cfm?staffid=336) 24 | -------------------------------------------------------------------------------- /site_libs/bootstrap-3.3.5/js/npm.js: -------------------------------------------------------------------------------- 1 | // This file is autogenerated via the `commonjs` Grunt task. You can require() this file in a CommonJS environment. 2 | require('../../js/transition.js') 3 | require('../../js/alert.js') 4 | require('../../js/button.js') 5 | require('../../js/carousel.js') 6 | require('../../js/collapse.js') 7 | require('../../js/dropdown.js') 8 | require('../../js/modal.js') 9 | require('../../js/tooltip.js') 10 | require('../../js/popover.js') 11 | require('../../js/scrollspy.js') 12 | require('../../js/tab.js') 13 | require('../../js/affix.js') -------------------------------------------------------------------------------- /styles.css: -------------------------------------------------------------------------------- 1 | /* Need to adjust the navbar behaviour so the navbar doesn't wrap */ 2 | .navbar-nav { 3 | position: fixed; 4 | left: 150px; 5 | width: 1000px; 6 | } 7 | 8 | .navbar-right { 9 | position: fixed; 10 | left: 80%; 11 | width: 300px; 12 | } 13 | 14 | .navbar-header { 15 | position: fixed; 16 | left: 30px; 17 | width: 97%; 18 | } 19 | 20 | .nav { 21 | font-size: 15px; 22 | } 23 | 24 | body { 25 | font-family: "Raleway","Helvetica Neue",Helvetica,Arial,sans-serif; 26 | line-height: 2; 27 | } 28 | 29 | div.scroll { 30 | background-color: #FFFFFF; 31 | height:225px; 32 | width: 100%; 33 | overflow-x: scroll; 34 | } 35 | 36 | blockquote { 37 | border-left:none; 38 | font-size: 1em; 39 | display: block; 40 | margin-top: .25em; 41 | margin-left: 20px; 42 | } 43 | 44 | h1 { 45 | padding-bottom: 0.5em; 46 | } 47 | 48 | .section { 49 | padding-bottom: 2em; 50 | } 51 | -------------------------------------------------------------------------------- /footer.html: -------------------------------------------------------------------------------- 1 |
2 | 20 | 21 | -------------------------------------------------------------------------------- /_site.yml: -------------------------------------------------------------------------------- 1 | name: fish-forecast-training-course 2 | output_dir: '.' 3 | navbar: 4 | title: Fish-Forecast 5 | left: 6 | - text: Welcome 7 | href: index.html 8 | - text: Syllabus 9 | href: syllabus.html 10 | - text: Set-up 11 | icon: fa-clone 12 | href: set-up.html 13 | - text: More Tutorials 14 | icon: fa-clipboard-list 15 | href: nextsteps.html 16 | - text: Daily Notes 17 | href: notes.html 18 | - text: Contact 19 | href: contact.html 20 | right: 21 | - icon: fa-home 22 | href: https://rverse-tutorials.github.io/Fish-Forecast-Training-Course/ 23 | - icon: fa-wrench 24 | href: https://rverse-tutorials.github.io/RWorkflow-Workshop 25 | - icon: fa-line-chart 26 | href: https://fish-forecast.github.io/Catch-Forecasting-INCOIS/ 27 | - icon: fa-github 28 | href: https://github.com/RVerse-Tutorials/Fish-Forecast-Training-Course 29 | output: 30 | html_document: 31 | theme: readable 32 | toc_depth: 2 33 | toc_float: 34 | collapsed: no 35 | highlight: textmate 36 | css: styles.css 37 | lib_dir: site_libs 38 | self_contained: no 39 | 40 | -------------------------------------------------------------------------------- /nextsteps.Rmd: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Continuing your learning" 3 | output: 4 | html_document: 5 | include: 6 | before_body: header.html 7 | --- 8 | 9 | Here are resources for continuing your learning of the topics that you studied this week: 10 | 11 | ## Intro to R 12 | 13 | * [Software Carpentry free tutorial](http://swcarpentry.github.io/r-novice-inflammation) 14 | 15 | * [Data Camp free tutorial](https://www.datacamp.com/courses/free-introduction-to-r). Takes about 4 hours. 16 | 17 | * You can also learn R straight from within R using the [swirl package](https://swirlstats.com/). This doesn't require internet access except to install the package. 18 | 19 | * Basic R introduction from [ComputerWorld](https://www.computerworld.com/article/2497143/business-intelligence/business-intelligence-beginner-s-guide-to-r-introduction.html). 20 | 21 | ## More R Workflow 22 | 23 | * Software Carpenter has a course that covers some of more advanced topics I did not cover on R workflow: data wrangling with dplyr, tidyverse, and more on RStudio projects. [Reproducible Research with R](http://swcarpentry.github.io/r-novice-gapminder/) 24 | 25 | * Eric Anderson produced a couple online courses on R workflow while with NOAA Fisheries. [R Reproducible Research 2015](http://eriqande.github.io/rep-res-web/) and [Reproducible Research 2017](https://eriqande.github.io/rep-res-eeb-2017/) 26 | 27 | ## Forecasting and Exponential Smoothing Models 28 | 29 | Rob J Hyndman (lead on the forecast package) and George Athanasopoulos have an excellent [online text on practical forecasting and exponential smoothing](https://otexts.org/fpp2/). 30 | 31 | ## Shiny Apps 32 | 33 | Start with RStudio's [online tutorial](https://shiny.rstudio.com/tutorial/written-tutorial/lesson1/) for shiny apps. 34 | 35 | 36 | -------------------------------------------------------------------------------- /data.Rmd: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Data" 3 | output: 4 | html_document: 5 | include: 6 | before_body: header.html 7 | --- 8 | 9 | We will be modeling and forecasting catch data however you can use the techniques we will learn on any regularly spaced time data. 10 | 11 | ```{r load_data, fig.align = "center", fig.height = 4, fig.width = 8, warning=FALSE, echo=FALSE} 12 | library(ggplot2) 13 | load("landings.RData") 14 | landings$log.metric.tons = log(landings$metric.tons) 15 | ggplot(landings, aes(x=Year, y=log.metric.tons)) + 16 | geom_line() + geom_point() + 17 | facet_wrap(~Species) 18 | ``` 19 | 20 | ## Data Format 21 | 22 | Your data should be in a simple csv (comma-separated) file with time (year, day, month, etc) and value: 23 | 24 | ``` 25 | Year, metric.tons 26 | 1964, 5449.2 27 | 1965, 4263.5 28 | 1966, 5146.4 29 | 1967, 7271.5 30 | 1968, 6352.5 31 | ``` 32 | 33 | If you have different locations or species, add that as a new column. 34 | 35 | ``` 36 | Year, metric.tons, species 37 | 1964, 5449.2, Anchovy 38 | 1965, 4263.5, Anchovy 39 | 1966, 5146.4, Anchovy 40 | 1967, 7271.5, Anchovy 41 | 1968, 6352.5, Anchovy 42 | 1964, 5449.2, Sardine 43 | 1965, 4263.5, Sardine 44 | 1966, 5146.4, Sardine 45 | 1967, 7271.5, Sardine 46 | 1968, 6352.5, Sardine 47 | ``` 48 | 49 | Here is an example with species and location. 50 | 51 | ``` 52 | Year, metric.tons, species, region 53 | 1964, 5449.2, Anchovy, North 54 | 1965, 4263.5, Anchovy, North 55 | 1966, 5146.4, Anchovy, North 56 | 1967, 7271.5, Anchovy, North 57 | 1968, 6352.5, Anchovy, North 58 | 1964, 5449.2, Sardine, North 59 | 1965, 4263.5, Sardine, North 60 | 1966, 5146.4, Sardine, North 61 | 1967, 7271.5, Sardine, North 62 | 1968, 6352.5, Sardine, North 63 | 1964, 5449.2, Sardine, South 64 | 1965, 4263.5, Sardine, South 65 | 1966, 5146.4, Sardine, South 66 | 1967, 7271.5, Sardine, South 67 | 1968, 6352.5, Sardine, South 68 | ``` -------------------------------------------------------------------------------- /index.Rmd: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Fish Forecast Training Course" 3 | output: 4 | html_document: 5 | include: 6 | before_body: header.html 7 | --- 8 | 9 | Welcome to the training programme on "Fish-catch Time-Series Forecasting with R" organized by 10 | International Training Centre for Operational Oceanography (ITCOocean) 11 | ESSO-Indian National Centre for Ocean Information Services(INCOIS), Hyderabad, India. 12 | [Course Announcement](http://www.incois.gov.in/ITCOocean/ftsf.jsp) 13 | 14 | Instructor: Dr. Eli Holmes, NOAA Fisheries Service, [Northwest Fisheries Science Center](https://www.nwfsc.noaa.gov/), Seattle, WA, USA. 15 | 16 | # Course Description 17 | 18 |
19 |
20 | This short course will be divided into a morning session on creating forecasting models for catch data and an afternoon session on Report-writing and Code documentation with R.
21 |
22 | The course will consist of short lectures and many practical labs where you will work with R to model data and prepare forecasts. You are encouraged to bring your own time-series data, for example yearly or monthly catch or count data, so that you can begin to model it during the course.
23 |
24 |
25 |
26 | In the afternoon, you will learn to write reports and websites with R and R Markdown so that you can easily share your work and document your work. You will learn how to easily prepare online books, reports and websites that integrate R and text.
27 |
28 | - Catch Forecasting [Web Link](https://fish-forecast.github.io/Catch-Forecasting-INCOIS/) -- [File Link](../Catch-Forecasting-INCOIS/index.html)
29 | - R Workflow [Web Link](https://rverse-tutorials.github.io/RWorkflow-Workshop/) -- [File Link](../RWorkflow-Workshop/index.html)
30 |
31 |
16 |
17 | ## Topics
18 |
19 | - Time-varying regression
20 | - Box-Jenkins (ARMA) Models
21 | - Exponential smoothing
22 | - Modelling time series with seasonality
23 | - Forecast diagnostics and accuracy metrics
24 |
25 |
26 | # Report-writing and code documentation with R (Afternoon)
27 |
28 |
29 |
30 | ## Topics
31 |
32 | - Basic workflow using RStudio, Git and GitHub
33 | - Intro to R Markdown
34 | - Creating simple websites from RStudio
35 | - Build an R package with RStudio
36 | - Creating simple websites from R packages on GitHub
37 | - Creating a book with R Markdown: Intro to Bookdown.
38 | - Creating and publishing RShiny applications
39 |
40 | # Catch Forecasting Lectures and Labs
41 |
42 |
50 |
51 | **Introduction**
52 |
53 | **Time-Varying Regression**
54 |
55 | These are the Rmd files for the Welcome website:
252 |https://rverse-tutorials.github.io/Fish-Forecast-Training-Course/
253 |Eli Holmes
345 |National Marine Fisheries Service
346 |Northwest Fisheries Science Center
347 |2725 Montlake Blvd East
348 |Seattle, WA
349 | 350 | 351 | 352 | 353 | 354 | 355 | 356 |Post questions and problems here.
345 | 346 | 347 | 365 | 366 | 367 | 368 | 369 |We will be modeling and forecasting catch data however you can use the techniques we will learn on any regularly spaced time data.
345 |
Your data should be in a simple csv (comma-separated) file with time (year, day, month, etc) and value:
349 |Year, metric.tons
350 | 1964, 5449.2
351 | 1965, 4263.5
352 | 1966, 5146.4
353 | 1967, 7271.5
354 | 1968, 6352.5
355 | If you have different locations or species, add that as a new column.
356 |Year, metric.tons, species
357 | 1964, 5449.2, Anchovy
358 | 1965, 4263.5, Anchovy
359 | 1966, 5146.4, Anchovy
360 | 1967, 7271.5, Anchovy
361 | 1968, 6352.5, Anchovy
362 | 1964, 5449.2, Sardine
363 | 1965, 4263.5, Sardine
364 | 1966, 5146.4, Sardine
365 | 1967, 7271.5, Sardine
366 | 1968, 6352.5, Sardine
367 | Here is an example with species and location.
368 |Year, metric.tons, species, region
369 | 1964, 5449.2, Anchovy, North
370 | 1965, 4263.5, Anchovy, North
371 | 1966, 5146.4, Anchovy, North
372 | 1967, 7271.5, Anchovy, North
373 | 1968, 6352.5, Anchovy, North
374 | 1964, 5449.2, Sardine, North
375 | 1965, 4263.5, Sardine, North
376 | 1966, 5146.4, Sardine, North
377 | 1967, 7271.5, Sardine, North
378 | 1968, 6352.5, Sardine, North
379 | 1964, 5449.2, Sardine, South
380 | 1965, 4263.5, Sardine, South
381 | 1966, 5146.4, Sardine, South
382 | 1967, 7271.5, Sardine, South
383 | 1968, 6352.5, Sardine, South
384 | Welcome to the training programme on “Fish-catch Time-Series Forecasting with R” organized by International Training Centre for Operational Oceanography (ITCOocean) ESSO-Indian National Centre for Ocean Information Services(INCOIS), Hyderabad, India. Course Announcement
345 |Instructor: Dr. Eli Holmes, NOAA Fisheries Service, Northwest Fisheries Science Center, Seattle, WA, USA.
346 |
This short course will be divided into a morning session on creating forecasting models for catch data and an afternoon session on Report-writing and Code documentation with R.
350 |The course will consist of short lectures and many practical labs where you will work with R to model data and prepare forecasts. You are encouraged to bring your own time-series data, for example yearly or monthly catch or count data, so that you can begin to model it during the course.
351 |
In the afternoon, you will learn to write reports and websites with R and R Markdown so that you can easily share your work and document your work. You will learn how to easily prepare online books, reports and websites that integrate R and text.
353 | 357 |———————————-
360 |Here are resources for continuing your learning of the topics that you studied this week:
345 |Data Camp free tutorial. Takes about 4 hours.
You can also learn R straight from within R using the swirl package. This doesn’t require internet access except to install the package.
Basic R introduction from ComputerWorld.
Software Carpenter has a course that covers some of more advanced topics I did not cover on R workflow: data wrangling with dplyr, tidyverse, and more on RStudio projects. Reproducible Research with R
Eric Anderson produced a couple online courses on R workflow while with NOAA Fisheries. R Reproducible Research 2015 and Reproducible Research 2017
Rob J Hyndman (lead on the forecast package) and George Athanasopoulos have an excellent online text on practical forecasting and exponential smoothing.
364 |Start with RStudio’s online tutorial for shiny apps.
368 |For building a package with roxygen documentation (the part that makes the help files for you), you need to tell RStudio to build that documentation when you click ‘Build and Reload’.
347 |Go to Tools > Project Options > Build Tools Then click the box that says the build documentation with roxygen. A pop-up window should appear. Click the box at the bottom that says to remake documentation when you click ‘Build and Reload’.
348 |Seasonal data. If you have seasonal data that you would like to analyze, please put in this format:
350 | Year Month metric.tons
351 | 2018 1 1
352 | 2018 2 2
353 | 2018 3 3
354 | ...
355 | 2019 1 4
356 | 2019 2 6
357 | 2019 3 NA
358 | Read in with this code:
359 |test <- read.csv("Data/test.csv", stringsAsFactors = FALSE)
360 | save(test, file="test.RData")
361 | To save data in R to a .csv file use the following:
365 |write.csv(landings, file="test.csv", row.names=FALSE, quote=FALSE)
366 | This works for data.frames, like landings, and also matrices:
367 |mat <- matrix(rnorm(10),5,2)
368 | colnames(mat) <- c("number 1", "number 2")
369 | write.csv(landings, file="test.csv", row.names=FALSE, quote=FALSE)
370 | The bookdown-demo repository has been edited so that it does not try to make a PDF. If you want that, there are instructions in the README.md file.
374 |Read in simple csv file named test.csv that looks like this
Year Species metric.tons
377 | 1 2018 Fish1 1
378 | 2 2019 Fish1 2
379 | 3 2018 Fish2 3
380 | 4 2019 Fish2 4
381 | 5 2018 Fish3 6
382 | 6 2019 Fish4 NA
383 | with this code:
384 |test <- read.csv("Data/test.csv", stringsAsFactors = FALSE)
385 | save(test, file="test.RData")
386 | Read in a file where the data are in columns. If your data (test.csv) look like this with each species (or site) across the columns:
388 |Year,Anchovy,Sardine,Chub mackerel,Horse mackerel,Mackerel,Jack Mackerel
389 | 1964,5449.2,12984.4,1720.7,4022.4,NA,NA
390 | 1965,4263.5,10611.1,1278.5,4158.3,NA,NA
391 | 1966,5146.4,11437.8,802.6,3012.1,NA,NA
392 | Use this code:
393 |library(reshape2)
394 | test <- read.csv("Data/test.csv", stringsAsFactors = FALSE)
395 | melt(test, id="Year", value.name="metric.tons", variable.name="Species")
396 | save(test, file="test.RData")
397 | If your data also have, say, a month (or qtr) column, use this code:
398 |library(reshape2)
399 | test <- read.csv("Data/test.csv", stringsAsFactors = FALSE)
400 | melt(test, id=c("Year","Month"), value.name="metric.tons", variable.name="Species")
401 | save(test, file="test.RData")
402 | If you have a response variable and multiple explanatory variables:
404 |Year, Anchovy, SST, Mackerel
405 | 1964, 5449.2, 24.4, 1720.7
406 | 1965, 4263.5, 30.1, 1278.5
407 | 1966, 5146.4, 23.8, 802.6
408 | Use this code:
409 |test <- read.csv("Data/test.csv", stringsAsFactors = FALSE)
410 | save(test, file="test.RData")
411 | Use this lm() model (or gam() etc):
fit <- lm(Anchovy ~ SST + Mackerel, data=test)
413 | What is a list? It is a object with multiple other types of objects ‘tied’ together.
415 |a <- list(ar=c(.8,.3), name="model", years=1:10)
416 | a
417 | ## $ar
418 | ## [1] 0.8 0.3
419 | ##
420 | ## $name
421 | ## [1] "model"
422 | ##
423 | ## $years
424 | ## [1] 1 2 3 4 5 6 7 8 9 10
425 | You can now reference the different objects in a.
a$ar
427 | ## [1] 0.8 0.3
428 | a$name
429 | ## [1] "model"
430 | Why is the arima.sim throwing an error sometimes? You must specify a stationary model and if you just randomly chose the \(\beta\)’s (AR parameters) and \(\theta\)’s (MA parameters) then you might be specifying a non-stationary model.
Please install the rmarkdown package. I forgot to include that.
436 |install.packages("rmarkdown")
437 | If you do not have LaTeX installed, you can install the tinytex package. Run these commands. This will allow you to make PDF files from R Markdown files. Some of you installed tinytex, but you need to run the 2nd command also to install LiveTeX.
439 |install.packages('tinytex')
440 | tinytex::install_tinytex()
441 | If your get an error saying package or repository unavailable when you are trying to install packages, try the following:
443 |chooseCRANmirror() from the command line. Pick any mirror.———————————
452 |

Introduction
467 |Time-Varying Regression
468 || Lectures | 477 |Labs | 478 |
|---|---|
| 1 Introduction to time-varying regression | 483 |1 Fit TV regression models to catch data | 484 |
| 2 Forecasts with a time-varying regression model | 487 |2 Create time-varying regression forecasts | 488 |
ARMA Models
492 || Lectures | 496 |Labs | 497 |
|---|---|
| 1 Introduction to ARMA Models | 502 |1 Intro to ARMA models and diagnostic plots | 503 |
| 2 Stationarity | 506 |2 Test the Greek catch data for stationarity | 507 |
| 3 Selecting Model Structure | 510 |3 Fit ARMA Models to the Greek catch data | 511 |
| 4 Fitting ARMA Models | 514 |4 Create and test forecasts | 515 |
| 5 Create and test forecasts | 518 |519 | |
Exponential Smoothing Models
523 || Lectures | 531 |Labs | 532 |
|---|---|
| 1 Introduction to Exponential Smoothing Models | 537 |1 Fit exponential smoothing models to data | 538 |
| 2 Selecting Model Structure | 541 |2 Create forecasts with exponential smoothing models | 542 |
| 3 Forecasting with exponential smoothing models | 545 |3 Testing models | 546 |
Seasonality
550 || Lectures | 558 |Labs | 559 |
|---|---|
| 1 Introduction to seasonality and approaches | 564 |1 Creating time-series objects with seasonality in R | 565 |
| 2 Seasonal time-vaying regression models | 568 |2 Seasonal exponential smoothing models | 569 |
| 3 Seasonal exponential smoothing models | 572 |573 | |