Time series analysis for the state-space model with r/stan [Documento eletrónico] / by Junichiro Hagiwara
Language: eng.Country: SG - Singapura.Publication: Singapore : Springer Nature Singapore, 2021Description: XIII, 347 p. : il.ISBN: 978-981-16-0711-0.Subject - Topical Name: Statistics | Mathematical statistics -- Data processing | Econometrics | Macroeconomics Online Resources:Click here to access onlineItem type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | |
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E-Books | Biblioteca NOVA FCT Online | Não Ficção | QA276.SPR FCT (Browse shelf(Opens below)) | 1 | Available | 95757 |
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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. .
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