3540719164

Forecasting with Exponential Smoothing: The State Space Approach (Repost)  eBooks & eLearning

Posted by AvaxGenius at Sept. 20, 2018
Forecasting with Exponential Smoothing: The State Space Approach (Repost)

Forecasting with Exponential Smoothing: The State Space Approach by Rob Hyndman
English | PDF | 2008 | 360 Pages | ISBN : 3540719164 | 3.14 MB

Exponential smoothing methods have been around since the 1950s, and are the most popular forecasting methods used in business and industry. Recently, exponential smoothing has been revolutionized with the introduction of a complete modeling framework incorporating innovations state space models, likelihood calculation, prediction intervals and procedures for model selection. In this book, all of the important results for this framework are brought together in a coherent manner with consistent notation. In addition, many new results and extensions are introduced and several application areas are examined in detail.

Forecasting with Exponential Smoothing: The State Space Approach  eBooks & eLearning

Posted by step778 at May 29, 2018
Forecasting with Exponential Smoothing: The State Space Approach

Rob Hyndman, Anne B. Koehler, J. Keith Ord, "Forecasting with Exponential Smoothing: The State Space Approach"
2008 | pages: 356 | ISBN: 3540719164 | PDF | 2,2 mb

3540719164Forecasting with Exponential Smoothing: The State Space Approach (Repost)  eBooks & eLearning

Posted by AvaxGenius at Sept. 19, 2019
3540719164Forecasting with Exponential Smoothing: The State Space Approach (Repost)

Forecasting with Exponential Smoothing: The State Space Approach by Rob Hyndman
English | PDF | 2008 | 360 Pages | ISBN : 3540719164 | 3.14 MB

Exponential smoothing methods have been around since the 1950s, and are the most popular forecasting methods used in business and industry. Recently, exponential smoothing has been revolutionized with the introduction of a complete modeling framework incorporating innovations state space models, likelihood calculation, prediction intervals and procedures for model selection. In this book, all of the important results for this framework are brought together in a coherent manner with consistent notation. In addition, many new results and extensions are introduced and several application areas are examined in detail.