Contents -- Preface -- 1.Getting started -- 2.Time series graphics -- 3.Time series decomposition -- 4.Time series features -- 5.The forecaster’s toolbox -- 6.Judgmental forecasts -- 7.Time series regression models -- 8.Exponential smoothing -- 9.ARIMA models -- 10. Dynamic regression models -- 11.Forecasting hierarchical and grouped time series -- 12.Advanced forecasting methods -- 13.Some practical forecasting issues -- Appendix: Using R -- Bibliography -- Index

Forecasting is required in many situations. Deciding whether to build another power generation plant in the next five years requires forecasts of future demand. Scheduling staff in a call centre next week requires forecasts of call volumes. Stocking an inventory requires forecasts of stock requirements. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly. Examples use R with many data sets taken from the authors' own consulting experience. In this third edition, all chapters have been updated to cover the latest research and forecasting methods. One new chapter has been added on time series features. The latest version of the book is freely available online at http: //OTexts.com/fpp3.