Time Series Analysis For The State Space Model With R-Stan

[Farid]

English | 360 pages | Springer; 1st ed. 2021 edition (August 31, 2021) | 9811607109 | EPUB,PDF | 48.42 Mb

Time Series Analysis For The State Space Model With R-Stan (Junichiro Hagiwara) (2021) English
Catergory: Computer Technology, Mathematics, Nonfiction

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.

🌞 Contents of Download:
📌 9811607109.epub (Junichiro Hagiwara) (2021) (39.58 MB)
📌 9811607109.pdf (0008471) (2021) (11.44 MB)

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⭐️ Time Series Analysis For The State Space Model With R-Stan ✅ (51.02 MB)
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