Testing for parameter constancy in non-Gaussian time series.

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. [ABSTRACT FROM AUTHOR]