Time Series Analysis by State Space Models by James Durbin, S. J. Koopman
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(Hardcover)
- Pub. Date: January 2001
- 253pp
- Sales Rank: 623,453
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Product Details
- Pub. Date: January 2001
- Publisher: Oxford University Press
- Format: Hardcover, 253pp
- Sales Rank: 623,453
- Series: Oxford Statistical Science Ser.
- ISBN-13: 9780198523543
- ISBN: 0198523548
- Edition Number: 2
Synopsis
State space time series analysis emerged in the 1960s in engineering, but its applications have spread to other fields. Durbin (statistics, London School of Economics and Political Science) and Koopman (econometrics, Free U., Amsterdam) extol the virtues of such models over the main analytical system currently used for time series data, Box-Jenkins' ARIMA. What distinguishes state space time models is that they separately model components such as trend, seasonal, regression elements and disturbance terms. Part I focuses on traditional and new techniques based on the linear Gaussian model. Part II presents new material extending the state space model to non-Gaussian observations.
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