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Item Details
Title: TIME SERIES ANALYSIS BY STATE SPACE METHODS
By: James Durbin, Siem Jan Koopman
Format: Hardback

List price: £115.00
Our price: £111.55
Discount:
3% off
You save: £3.45
ISBN 10: 019964117X
ISBN 13: 9780199641178
Availability: Usually dispatched within 1-3 weeks.
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Publisher: OXFORD UNIVERSITY PRESS
Pub. date: 3 May, 2012
Edition: 2nd Revised edition
Series: Oxford Statistical Science Series 38
Pages: 368
Description: 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.
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.
Illustrations: 34 b/w illustrations
Publication: UK
Imprint: Oxford University Press
Returns: Returnable
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