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This repository documents my learning journey in time series analysis. It contains class notes, practice scripts, and small projects where I experimented with different forecasting models. The goal is to build strong foundations in time series forecasting and apply them to real-world datasets.

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Time Series Analysis – R Notes & Exercises

📌 Overview

This repository contains a collection of R scripts from my Time Series Analysis course. It includes exercises, practice code, and small projects where I explored time series forecasting techniques. The repo serves both as my learning archive and a demonstration of my hands-on work with forecasting models in R.


📂 What’s Inside

The repository includes scripts covering a wide range of topics:

  • Decomposition of Time Series
    • Classical, STL, SEATS, and X-11 decomposition
  • Forecasting Methods
    • ARIMA and SARIMA
    • Exponential smoothing (SES, Holt, Holt-Winters)
    • Neural network forecasting (NNETAR)
    • Naive forecasting methods
  • Evaluation & Diagnostics
    • Ljung-Box test
    • Accuracy metrics and error evaluation
    • Box-Cox transformations
  • Regression Models
    • Time series regression
    • Dynamic regression models
  • Advanced Topics
    • Hierarchical and grouped forecasting
    • Seasonal time series graphics and visualization
  • Practice & Notes
    • Class assignments
    • Exam review scripts
    • Small mini-projects

About

This repository documents my learning journey in time series analysis. It contains class notes, practice scripts, and small projects where I experimented with different forecasting models. The goal is to build strong foundations in time series forecasting and apply them to real-world datasets.

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