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Time Series Analysis by State Space Methods: Second Edition (Oxford Statistical Science Series) - Hardcover
Synopsis
This new edition updates Durbin & Koopman's important text on the state space approach to time series analysis. The distinguishing feature of state space time series models is that observations are regarded as made up of distinct components such as trend, seasonal, regression elements and disturbance terms, each of which is modelled separately. The techniques that emerge from this approach are very flexible and are capable of handling a much wider range of problems than the main analytical system currently in use for time series analysis, the Box-Jenkins ARIMA system. Additions to this second edition include the filtering of nonlinear and non-Gaussian series.
Part I of the book obtains the mean and variance of the state, of a variable intended to measure the effect of an interaction and of regression coefficients, in terms of the observations.
Part II extends the treatment to nonlinear and non-normal models. For these, analytical solutions are not available so methods are based on simulation.
"synopsis" may belong to another edition of this title.
About the Author
James Durbin was Professor of Statistics at the London School of Economics, President of the Royal Statistical Society and President of the International Statistical Institute. He was awarded the society's bronze, silver and gold medals for his contribution to statistics. He is a fellow of the British Academy.
Siem Jan Koopman has been Professor of Econometrics at the Free University in Amsterdam and research fellow at the Tinbergen Institute since 1999. He fullfills editorial duties at the Journal of Applied Econometrics, the Journal of Forecasting, the Journal of Multivariate Analysis and Statistica Sinica.
Review
Review from previous edition: "...provides an up-to-date exposition and comprehensive treatment of state space models in time series analysis...This book will be helpful to graduate students and applied statisticians working in the area of econometric modelling as well as researchers in the
areas of engineering, medicine and biology where state space models are used."
--Journal of the Royal Statistical Society
"About this title" may belong to another edition of this title.
- PublisherOxford University Press
- Publication date2012
- ISBN 10 019964117X
- ISBN 13 9780199641178
- BindingHardcover
- LanguageEnglish
- Edition number2
- Number of pages368
- Rating
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Time Series Analysis by State Space Methods: Second Edition
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Time Series Analysis by State Space Methods: Second Edition (Oxford Statistical Science Series)
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Time Series Analysis by State Space Methods: Second Edition: 38 (Oxford Statistical Science Series)
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Hardcover. Condition: new. Hardcover. This new edition updates Durbin & Koopman's important text on the state space approach to time series analysis. The distinguishing feature of state space time series models is that observations are regarded as made up of distinct components such as trend, seasonal, regression elements and disturbance terms, each of which is modelled separately. The techniques that emerge from this approach are very flexible and are capable of handling a much wider range ofproblems than the main analytical system currently in use for time series analysis, the Box-Jenkins ARIMA system. Additions to this second edition include the filtering of nonlinear and non-Gaussianseries.Part I of the book obtains the mean and variance of the state, of a variable intended to measure the effect of an interaction and of regression coefficients, in terms of the observations.Part II extends the treatment to nonlinear and non-normal models. For these, analytical solutions are not available so methods are based on simulation. This new edition updates Durbin & Koopman's important text on the state space approach to time series analysis providing a more comprehensive treatment, including the filtering of nonlinear and non-Gaussian series. The book provides an excellent source for the development of practical courses on time series analysis. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780199641178
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