Testing for serial dependence in time series models of counts

Robert Jung () and Andrew Tremayne

Journal of Time Series Analysis, 2003, vol. 24, issue 1, 65-84

Abstract: Abstract. In analysing time series of counts, the need to test for the presence of a dependence structure routinely arises. Suitable tests for this purpose are considered in this paper. Their size and power properties are evaluated under various alternatives taken from the class of INARMA processes. We find that all the tests considered except one are robust against extra binomial variation in the data and that tests based on the sample autocorrelations and the sample partial autocorrelations can help to distinguish between integer‐valued first‐order and second‐order autoregressive as well as first‐order moving average processes.

Date: 2003
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