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Time Series Analysis by State Space Methods by James Durbin, Siem Jan Koopman, (2001) Publisher: Oxford University Press ISBN: 0-19852354-8 Pages: 253 pages Price: £48.00+ p&p |
Contents Book Order Form Table of Contents |
| Table of Contents Part I - The linear Gaussian state space models; Preface to Part I 1 Introduction 2 Local level model 3 Linear Gaussian state space models 4 Filtering, smoothing and forecasting 5 Initialisation of filter and smoother 6 Further computational aspects 7 Maximum likelihood estimation 8 Bayesian analysis 9 Illustrations of the use of the linear Gaussian model Part II - Non-Gaussian and nonlinear state space models; Preface to Part II 10 Non-Gaussian and nonlinear state space models 11 Importance sampling 12 Analysis from a classical standpoint 13 Analysis from a Bayesian standpoint 14 Non-Gaussian and nonlinear illustrations References |
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