A goodness-of-fit test for Poisson count processes

Fokianos, K. and Neumann, M.H. (2013) A goodness-of-fit test for Poisson count processes. Electronic Journal of Statistics, 7 (1). pp. 793-819. ISSN 1935-7524

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Abstract

We are studying a novel class of goodness-of-fit tests for parametric count time series regression models. These test statistics are formed by considering smoothed versions of the empirical process of the Pearson residuals. Our construction yields test statistics which are consistent against Pitman’s local alternatives and they converge weakly at the usual parametric rate. To approximate the asymptotic null distribution of the test statistics, we propose a parametric bootstrap method and we study its properties. The methodology is applied to simulated and real data.

Item Type:
Journal Article
Journal or Publication Title:
Electronic Journal of Statistics
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2613
Subjects:
?? statistics and probability ??
ID Code:
127762
Deposited By:
Deposited On:
25 Sep 2018 14:26
Refereed?:
Yes
Published?:
Published
Last Modified:
15 Jul 2024 18:22