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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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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 22 January 2022

Special cases of nonlinear and non-Gaussian models

Special cases of nonlinear and non-Gaussian models

Chapter:
(p.208) (p.209) 9 Special cases of nonlinear and non-Gaussian models
Source:
Time Series Analysis by State Space Methods
Author(s):

J. Durbin

S.J. Koopman

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199641178.003.0009

This chapter discusses the range of non-Gaussian and nonlinear models that can be analysed using the methods of Part II. The chapter is organized as follows. Section 9.2 considers an important special form of the general linear non-Gaussian model. Sections 9.3–9.6 examine special cases of some subclasses of models of interest, namely exponential family models, heavy-tailed models, stochastic volatility model and other financial models. Section 9.7 describes some classes of nonlinear models of interest.

Keywords:   exponential family models, heavy-tailed models, stochastic volatility model, nonlinear models

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