A Goodness-of-Fit Test for Integer-Valued Autoregressive Processes

Sebastian Schweer

Journal of Time Series Analysis, 2016, vol. 37, issue 1, 77-98

Abstract: type="main" xml:id="jtsa12138-abs-0001"> For autoregressive count data time series, a goodness-of-fit test based on the empirical joint probability generating function is considered. The underlying process is contained in a general class of Markovian models satisfying a drift condition. Asymptotic theory for the test statistic is provided, including a functional central limit theorem for the non-parametric estimation of the stationary distribution and a parametric bootstrap method. Connections between the new approach and existing tests for count data time series based on moment estimators appear in limiting scenarios. Finally, the test is applied to a real data set.

Date: 2016
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Citations: View citations in EconPapers (8)

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