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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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Non-Gaussian and nonlinear illustrations

Non-Gaussian and nonlinear illustrations

Chapter:
(p.312) 14 Non-Gaussian and nonlinear illustrations
Source:
Time Series Analysis by State Space Methods
Author(s):

J. Durbin

S.J. Koopman

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199641178.003.0014

This chapter discusses examples which illustrate the methods that were developed in Part II for analysing observations using non-Gaussian and nonlinear state space models. These include the monthly number of van drivers killed in road accidents in Great Britain modelled by a Poisson distribution; the usefulness of the t-distribution for modelling observation errors in a gas consumption series containing outliers; the volatility of exchange rate returns; and fitting a binary model to the results of the annual boat race between teams of the universities of Oxford and Cambridge.

Keywords:   non-Gaussian models, nonlinear models, Poisson distribution, t-distribution, volatility, binary model

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