(Time Series) Forecasting: Principles & Practice (in R)

I stumbled across this open access book by Rob Hyndman, the god of time series, and George Athanasopoulos, a colleague statistician / econometrician at Monash University in Melbourne Australia.

Hyndman and Athanasopoulos provide a comprehensive introduction to forecasting methods, accessible and relevant among others for business professionals without any formal training in the area. All R examples in the book assume work build on the fpp2 R package. fpp2 includes all datasets referred to in the book and depends on other R packages including forecast and ggplot2.

Some examples of the analyses you can expect to recreate, ignore the agricultural topic for now ; )

Monthly milk production per cow.
One of the example analysis you will recreate by following the book (Figure 3.3)
Forecasts of egg prices using a random walk with drift applied to the logged data.
You will be forecasting price data using different analyses and adjustments (Figure 3.4)

I highly recommend this book to any professionals or students looking to learn more about forecasting and time series modelling. There is also a DataCamp course based on this book. If you got value out of this free book, be sure to buy a hardcopy as well.

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