After years of saying that I was going to write a book to replace Makridakis, Wheelwright and Hyndman (1998), I’m finally ready to make an announcement!

My new book is **Forecasting: principles and practice**, co-authored with George Athanasopoulos. It is available online and free-of-charge. We have written about 2/3 of the book so far (all of which is already available online), and we plan to finish it by the end of 2012. We hope to make a print version of the book available on Amazon in early 2013.

This textbook is intended to provide a comprehensive introduction to forecasting methods and present enough information about each method for readers to use them sensibly. We don’t attempt to give a thorough discussion of the theoretical details behind each method, although the references at the end of each chapter will fill in many of those details. We use R throughout the book and we intend students to learn how to forecast with R.

The book has it’s own R package: fpp. This contains all the data sets used in the book, and also loads a few other packages that are necessary to complete the examples.

The book is different from other forecasting textbooks in several ways.

- It is free and online, making it accessible to a wide audience.
- It is based around the forecast package for R.
- It is continuously updated. You don’t have to wait until the next edition for errors to be removed or new methods to be discussed. We will update the book frequently.
- There are dozens of real data examples taken from our own consulting practice. We have worked with hundreds of businesses and organizations helping them with forecasting issues, and this experience has contributed directly to many of the examples given here, as well as guiding our general philosophy of forecasting.
- We emphasise graphical methods more than most forecasters. We use graphs to explore the data, analyse the validity of the models fitted and present the forecasting results.

*Related*

To

**leave a comment** for the author, please follow the link and comment on their blog:

** Research tips » R**.

R-bloggers.com offers

**daily e-mail updates** about

R news and

tutorials on topics such as:

Data science,

Big Data, R jobs, visualization (

ggplot2,

Boxplots,

maps,

animation), programming (

RStudio,

Sweave,

LaTeX,

SQL,

Eclipse,

git,

hadoop,

Web Scraping) statistics (

regression,

PCA,

time series,

trading) and more...

If you got this far, why not

__subscribe for updates__ from the site? Choose your flavor:

e-mail,

twitter,

RSS, or

facebook...

**Tags:** forecasting, R, references, Research tips, Writing