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Time Series Analysis by State Space Methods Second Edition

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ISBN-10: 019964117X

ISBN-13: 9780199641178

Edition: 2nd 2012

Authors: James Durbin, Siem Jan Koopman

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Book details

Edition: 2nd
Copyright year: 2012
Publisher: Oxford University Press
Publication date: 5/3/2012
Binding: Hardcover
Pages: 400
Size: 6.34" wide x 9.25" long x 1.01" tall
Weight: 1.496
Language: English

Siem Jan Koopman is Professor of Econometrics at the Free University Amsterdam and Research Fellow of Tinbergen Institute, Amsterdam. He has published in international journals and is co-author of Time Series Analysis by State Space Models (with J. Durbin, 2001).

Introduction
The linear state space model
Local level model
Linear Gaussian state space models
Filtering, smoothing and forecasting
Initialisation of Filter and smoother
Further computational aspects
Maximum likelihood estimation of parameters
Illustrations of the use of the linear Gaussian model
Non-Gaussian and nonlinear state space models
Special cases of nonlinear and non-Gaussian models
Approximate filtering and smoothing
Importance sampling for smoothing
Particle filtering
Bayesian estimation of parameters
Non-Gaussian and nonlinear illustrations
Subject Index