Forecasting: principles and practice

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 second edition, all chapters have been updated to cover the latest research and forecasting methods. Three new chapters have been added on dynamic regression forecasting, hierarchical forecasting and practical forecasting issues. The latest version of the book is freely available online at http://OTexts.com/fpp2.

• Practical Time Series Forecasting with R: A Hands-On Guide [2nd Edition] (Practical Analytics)
• Introductory Time Series with R (Use R!)
• Applied Predictive Modeling
• An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
• Time Series Analysis and Its Applications: With R Examples (Springer Texts in Statistics)
• Analysis of Categorical Data with R (Chapman & Hall/CRC Texts in Statistical Science)
• Introduction to Time Series Analysis and Forecasting (Wiley Series in Probability and Statistics)
• An Introduction to Analysis of Financial Data with R
• The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
• Business Forecasting: Practical Problems and Solutions (Wiley and SAS Business Series)