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

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.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Release date:	September 2022
First published:	2021
Authors:	Junichiro Hagiwara
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	347
Edition:	1st ed. 2021
ISBN-13:	978-981-16-0713-4
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Business & Economics > Economics > Macroeconomics > General Books > Business & Economics > Economics > Econometrics > General Books > Computing & IT > Computer software packages > Other software packages > Mathematical & statistical software Promotions
LSN:	981-16-0713-3
Barcode:	9789811607134

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