Time Series Analysis for the State-Space Model with R/Stan (1st ed. 2021)

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Synopsis
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.
Copyright:
2021

Book Details

Book Quality:
Publisher Quality
ISBN-13:
9789811607110
Related ISBNs:
9789811607103
Publisher:
Springer Singapore, Singapore
Date of Addition:
Copyrighted By:
Springer Nature Singapore Pte Ltd.
Adult content:
No
Language:
English
Has Image Descriptions:
No
Categories:
Nonfiction, Computers and Internet, Business and Finance, Mathematics and Statistics
Submitted By:
Bookshare Staff
Usage Restrictions:
This is a copyrighted book.

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