This repository provides replication files for the book "Forecasting: Principles and Practice (3rd edition)" by Hyndman & Athanasopoulos, using the Gretl software. It is intended to help readers reproduce the examples and analyses from the book with Gretl, offering scripts and data files that mirror the R-based workflows presented in the original text. The repository is a resource for students, educators, and practitioners interested in learning forecasting methods with open-source tools.
E-book online available at https://otexts.com/fpp3/. It uses the fpp3 package for R.
There is also a new Python edition of the book, available at https://otexts.com/fpppy entitled "Forecasting: Principles and Practice, the Pythonic Way" (out since autumn 2025).
However, the replication files in this repository are based on the R version of the book.
The data files used in the replication scripts are available in the data/ folder. There are CSV files as well as Gretl data files (*.gdt). Both formats can be opened directly in Gretl.
7.1 The linear model -- Gretl replication file
7.2 Least squares estimation -- Gretl replication file
7.3 Evaluating the regression model -- Gretl replication file
7.4 Some useful predictors -- Gretl replication file
7.5 Selecting predictors -- Gretl replication file
7.6 Forecasting with regression -- Gretl replication file
7.7 Non-linear regression -- Gretl replication file
9.1 Stationarity and differencing -- Gretl replication file
9.3 Autoregressive models -- Gretl replication file
9.4 Moving average models -- Gretl replication file
9.5 Non-seasonal ARIMA models -- Gretl replication file
9.9 Seasonal ARIMA models -- Gretl replication file
9.10 ARIMA and ETS models -- NOT IMPLEMENTED, YET -- Gretl replication file
10.2 Regression with ARIMA errors using Gretl -- Gretl replication file
10.3 Forecasting -- Gretl replication file