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Time Series Analysis by State Space MethodsSecond Edition$
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James Durbin and Siem Jan Koopman

Print publication date: 2012

Print ISBN-13: 9780199641178

Published to Oxford Scholarship Online: December 2013

DOI: 10.1093/acprof:oso/9780199641178.001.0001

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Further computational aspects

Further computational aspects

Chapter:
(p.147) 6 Further computational aspects
Source:
Time Series Analysis by State Space Methods
Author(s):

J. Durbin

S.J. Koopman

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199641178.003.0006

This chapter continues the discussion of the computational aspects of filtering and smoothing. It explains the estimation of a regression component of the model and intervention components; the square root filter and smoother which may be used when the Kalman filter and smoother show signs of numerical instability; how multivariate time series can be treated as univariate series by bringing elements of the observational vectors into the system one at a time, with computational savings relative to the multivariate treatment in some cases; and further modifications where the observation vector is high-dimensional. The chapter concludes by discussing computer packages for state space methods.

Keywords:   filtering, smoothing, regression estimation, square root filter, smother, multivariate time series, univariate series

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