Time Series Analysis by State Space Methods

This excellent text provides a comprehensive treatment of 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 disturbence te...

Full description

Saved in:
Bibliographic Details
Main Authors Koopman, Siem Jan, Durbin, James
Format Book
LanguageEnglish
Published Oxford University Press 2001
SeriesOUP Catalogue
Online AccessGet more information

Cover

More Information
Summary:This excellent text provides a comprehensive treatment of 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 disturbence 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. The book provides an excellent source for the development of practical courses on time series analysis.
ISBN:0198523548
9780198523543