Time Series Analysis for the State-Space Model With R/Stan
1st Edition 2021
Hardback (31 Aug 2021)
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This book provides a comprehensive and concrete illustration of time series analysis focusing on the state-space model, which has recently attracted increasing attention in a broad range of fields. The major feature of the book lies in its consistent Bayesian treatment regarding whole combinations of batch and sequential solutions for linear Gaussian and general state-space models: MCMC and Kalman/particle filter. The reader is given insight on flexible modeling in modern time series analysis. The main topics of the book deal with the state-space model, covering extensively, from introductory and exploratory methods to the latest advanced topics such as real-time structural change detection. Additionally, a practical exercise using R/Stan based on real data promotes understanding and enhances the reader's analytical capability.
Book information
ISBN: | 9789811607103 |
Publisher: | Springer Nature Singapore |
Imprint: | Springer |
Pub date: | 31 Aug 2021 |
Edition: | 1st Edition 2021 |
Language: | English |
Number of pages: | 347 |
Weight: | 711g |
Height: | 235mm |
Width: | 155mm |
Spine width: | 21mm |