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DETECTING AND MODELLING SERIAL DEPENDENCE IN NONGAUSSIAN AND NONLINEAR TIME SERIES

Part of: Nonparametric inference Linear inference, regression Inference from stochastic processes Parametric inference

Published online by Cambridge University Press:  02 November 2016

JIEYI HE
JIEYI HE*
Affiliation:
School of Mathematics and Statistics, University of New South Wales, Sydney, New South Wales 2052, Australia email jieyi.he@yahoo.com.au
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Abstract

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Keywords

observation-driven modelsparameter-driven modelsserial dependencescore testsupremum testasymptotic theory

MSC classification

Primary: 62M10: Time series, auto-correlation, regression, etc.
Secondary: 62F12: Asymptotic properties of estimators 62G08: Nonparametric regression 62J12: Generalized linear models
Type
Abstracts of Australasian PhD Theses
Information
Bulletin of the Australian Mathematical Society , Volume 95 , Issue 1 , February 2017 , pp. 169 - 171
Copyright
© 2016 Australian Mathematical Publishing Association Inc.