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Time Series Analysis for the State-Space Model with R/Stan / by Junichiro Hagiwara.
Springer Nature - Springer Mathematics and Statistics eBooks 2021 English International Available online
View online- Format:
- Book
- Author/Creator:
- Hagiwara, Junichiro, author.
- Language:
- English
- Subjects (All):
- Statistics.
- Mathematical statistics--Data processing.
- Mathematical statistics.
- Econometrics.
- Macroeconomics.
- Applied Statistics.
- Statistics and Computing.
- Bayesian Inference.
- Statistical Theory and Methods.
- Quantitative Economics.
- Macroeconomics and Monetary Economics.
- Local Subjects:
- Applied Statistics.
- Statistics and Computing.
- Bayesian Inference.
- Statistical Theory and Methods.
- Quantitative Economics.
- Macroeconomics and Monetary Economics.
- Physical Description:
- 1 online resource (350 pages)
- Edition:
- 1st ed. 2021.
- Place of Publication:
- Singapore : Springer Nature Singapore : Imprint: Springer, 2021.
- Summary:
- 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:
- Introduction
- Fundamental of probability and statistics
- Fundamentals of handling time series data with R
- Quick tour of time series analysis
- State-space model
- State estimation in the state-space model
- Batch solution for linear Gaussian state-space model
- Sequential solution for linear Gaussian state-space model
- Introduction and analysis examples of a well-known component model
- Batch solution for general state-space model
- Sequential solution for general state-space model
- Example of applied analysis in general state-space model.
- ISBN:
- 9789811607110
- 9811607117
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