Rob J. Hyndman Livres

Forecasting plays a crucial role in diverse scenarios, from energy production planning to call center staffing and inventory management. This textbook offers an in-depth introduction to various forecasting methods, equipping readers with practical knowledge for effective application. Enhanced with updated research and techniques in its third edition, it includes a new chapter on time series features. Real-world examples utilize R and data from the authors' consulting experiences, making it a valuable resource for both students and professionals. The latest edition is freely accessible online.

Exponential smoothing methods have been around since the 1950s, and are still the most popular forecasting methods used in business and industry. However, a modeling framework incorporating stochastic models, likelihood calculation, prediction intervals and procedures for model selection, was not developed until recently. This book brings together all of the important new results on the state space framework for exponential smoothing. It will be of interest to people wanting to apply the methods in their own area of interest as well as for researchers wanting to take the ideas in new directions. Part 1 provides an introduction to exponential smoothing and the underlying models. The essential details are given in Part 2, which also provide links to the most important papers in the literature. More advanced topics are covered in Part 3, including the mathematical properties of the models and extensions of the models for specific problems. Applications to particular domains are discussed in Part 4.

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