├── Double Exponential Smoothing (Holt's Method) - Monthly and Annual Forescast.ipynb
├── LICENSE
├── Moving Averages - Monthly Forescast.ipynb
├── README.md
├── Simple Exponential Smoothing - Monthly and Annual Forecast.ipynb
└── Triple Exponential Smoothing (Holt-Winters Method) - Monthly and Annual Forescast.ipynb


/LICENSE:
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 1 | MIT License
 2 | 
 3 | Copyright (c) 2025 Renato Maynard Etchepare
 4 | 
 5 | Permission is hereby granted, free of charge, to any person obtaining a copy
 6 | of this software and associated documentation files (the "Software"), to deal
 7 | in the Software without restriction, including without limitation the rights
 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 | 
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 | 
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 | 


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/README.md:
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 1 | # 📈 Time Series Forecasting Methods
 2 | 
 3 | This repository contains Python implementations of essential **time series forecasting methods**, including:
 4 | 
 5 | - ✅ **Simple Exponential Smoothing (SES)**
 6 | - ✅ **Double Exponential Smoothing (Holt's Method)**
 7 | - ✅ **Triple Exponential Smoothing (Holt-Winters Method)**
 8 | - ✅ **Moving Averages**
 9 | 
10 | The goal of this repository is to **demonstrate and compare forecasting techniques** using synthetic demand data with trend and seasonality.
11 | 
12 | ---
13 | 
14 | ## 📊 Methods Covered
15 | 
16 | ### 1. Simple Exponential Smoothing (SES)
17 | - Suitable for data without trend or seasonality.
18 | - Forecasts future values as a constant level, adjusted with a smoothing factor.
19 | 
20 | ### 2. Double Exponential Smoothing (Holt's Method)
21 | - Handles data with a trend.
22 | - Forecast incorporates both level and trend components.
23 | 
24 | ### 3. Triple Exponential Smoothing (Holt-Winters Method)
25 | - Handles data with both trend and seasonality.
26 | - Forecasts are adjusted for seasonal patterns (additive and multiplicative).
27 | 
28 | ### 4. Moving Averages
29 | - Simple method using the mean of past observations.
30 | - Used for short-term forecasts and smoothing series.
31 | 
32 | ---
33 | 
34 | ## 🚀 Features
35 | 
36 | - ✅ **Self-contained synthetic datasets** — no external files required.
37 | - ✅ **Clean, well-commented Python code** ready for educational and practical use.
38 | - ✅ Automatic **forecast extension** for future periods.
39 | - ✅ **Graphical visualizations** for each method.
40 | - ✅ **Error analysis**: MSE, MAPE, MAD.
41 | - ✅ Statistical tests (Ljung-Box) for autocorrelation checking.
42 | 
43 | ---
44 | 
45 | ## 🛠️ Technologies Used
46 | 
47 | - **Python 3.x**
48 | - **pandas** — Data manipulation
49 | - **NumPy** — Numerical computations
50 | - **matplotlib** — Plotting and visualization
51 | - **scikit-learn** — Error metrics (MSE, MAPE, MAD)
52 | - **statsmodels** — Time series models and statistical tests
53 | 
54 | ---
55 | 
56 | ## ✅ How to Run
57 | 
58 | 1. **Clone this repository:**
59 | ```bash
60 | git clone https://github.com/RenatoMaynard/time-series-forecasting-methods.git
61 | ```
62 | 2. **Install required packages**
63 | ```bash
64 | pip install pandas matplotlib numpy scikit-learn statsmodels
65 | ```
66 | 
67 | ---
68 | 
69 | ## Acknowledgments
70 | This project is designed for educational purposes to understand time series forecasting techniques in Python.
71 | 
72 | ---
73 | 
74 | ## ⚠️ Disclaimer
75 | This project is for educational purposes only. Errors may exist. Please report issues or contribute improvements via pull requests.
76 | 
77 | ---
78 | 
79 | ## License
80 | This project is licensed under the **MIT License** — see the [LICENSE](LICENSE) file for details.
81 | 
82 |    
83 | 


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