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2013 A goodness-of-fit test for Poisson count processes
Konstantinos Fokianos, Michael H. Neumann
Electron. J. Statist. 7(none): 793-819 (2013). DOI: 10.1214/13-EJS790

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.

Citation

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Konstantinos Fokianos. Michael H. Neumann. "A goodness-of-fit test for Poisson count processes." Electron. J. Statist. 7 793 - 819, 2013. https://doi.org/10.1214/13-EJS790

Information

Published: 2013
First available in Project Euclid: 25 March 2013

zbMATH: 1327.62455
MathSciNet: MR3040560
Digital Object Identifier: 10.1214/13-EJS790

Subjects:
Primary: 60G10, 62M07
Secondary: 62F40

Rights: Copyright © 2013 The Institute of Mathematical Statistics and the Bernoulli Society

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