Jump to ContentJump to Main Navigation
Modelling Nonlinear Economic Time Series$
Users without a subscription are not able to see the full content.

Timo Teräsvirta, Dag Tjøstheim, and Clive W. J. Granger

Print publication date: 2010

Print ISBN-13: 9780199587148

Published to Oxford Scholarship Online: May 2011

DOI: 10.1093/acprof:oso/9780199587148.001.0001

Show Summary Details
Page of

PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2020. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 29 November 2020

9 Time‐varying parameters and state space models

9 Time‐varying parameters and state space models

(p.219) 9 Time‐varying parameters and state space models
Modelling Nonlinear Economic Time Series

Timo Teräsvirta

Dag Tjøstheim (Contributor Webpage)

W. J. Granger

Oxford University Press

Linear state space models have become popular in time series, and there are applications to many fields. The Kalman filter is often a fundamental tool. In this chapter it is shown that there are extensions of these concepts to a nonlinear framework through such devices as the extended Kalman filter and particle filters. Hidden Markov chains represents an alternative but related technique, where parameters are replaced by stochastic processes; i.e., Markov chains. The chapter also contains a short section on estimating these types of models.

Keywords:   state space, Kalman filter, particle filter, hidden Markov chains

Oxford Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.

Please, subscribe or login to access full text content.

If you think you should have access to this title, please contact your librarian.

To troubleshoot, please check our FAQs , and if you can't find the answer there, please contact us .