Testing for Parameter Constancy in Non‐Gaussian Time Series

13 Pages Posted: 23 Dec 2012

See all articles by Lu Han

Lu Han

University of Liverpool

Brendan P.M. McCabe

University of Liverpool - Management School (ULMS)

Date Written: January 2013

Abstract

This paper investigates testing for parameter constancy in models for non‐Gaussian time series. Models for discrete valued count time series are investigated as well as more general models with autoregressive conditional expectations. Both sup‐tests and CUSUM procedures are suggested depending on the complexity of the model being used. The asymptotic distribution of the CUSUM test is derived for a general class of conditional autoregressive models.

Keywords: Non‐Gaussian Time Series, Discrete Valued Count Time Series, sup‐Test, CUSUM Test

Suggested Citation

Han, Lu and McCabe, Brendan P.M., Testing for Parameter Constancy in Non‐Gaussian Time Series (January 2013). Journal of Time Series Analysis, Vol. 34, Issue 1, pp. 17-29, 2013, Available at SSRN: https://ssrn.com/abstract=2193198 or http://dx.doi.org/10.1111/j.1467-9892.2012.00810.x

Lu Han

University of Liverpool

Chatham Street
Liverpool, L69 7ZA
United Kingdom

Brendan P.M. McCabe

University of Liverpool - Management School (ULMS) ( email )

Chatham Street
Liverpool, L69 7ZH
United Kingdom

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