Publisher's Synopsis
Practical Time Series Forecasting with R: A Hands-On Guide, Third Edition provides an applied approach to time-series forecasting. Forecasting is an essential component of predictive analytics. The book introduces popular forecasting methods and approaches used in a variety of business applications.
The book offers clear explanations, practical examples, and end-of-chapter exercises and cases. Readers will learn to use forecasting methods using the free open-source R software to develop effective forecasting solutions that extract business value from time series data. This edition features the R fable package, full color, enhanced organization, and new material. It includes:- Popular forecasting methods including smoothing algorithms, regression models, ARIMA, neural networks, deep learning, and ensembles
- A practical approach to evaluating the performance of forecasting solutions
- A business-analytics exposition focused on linking time-series forecasting to business goals
- Guided cases for integrating the acquired knowledge using real data
- End-of-chapter problems to facilitate active learning
- Data, R code, and instructor materials on companion website
- Affordable and globally-available textbook, available in hardcover, paperback, and Kindle formats
