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Monte Carlo exact goodness‐of‐fit tests for nonhomogeneous Poisson processes

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  • Bo H. Lindqvist
  • Bjarte Rannestad

Abstract

Nonhomogeneous Poisson processes (NHPPs) are often used to model failure data from repairable systems, and there is thus a need to check model fit for such models. We study the problem of obtaining exact goodness‐of‐fit tests for parametric NHPPs. The idea is to use conditional tests given a sufficient statistic under the null hypothesis model. The tests are performed by simulating conditional samples given the sufficient statistic. Algorithms are presented for testing goodness‐of‐fit for the power law and the log‐linear law NHPP models. It is noted that while exact algorithms for the power law case are well known in the literature, the availability of such algorithms for the log‐linear case seems to be less known. A data example, as well as simulations, are considered. Copyright © 2010 John Wiley & Sons, Ltd.

Suggested Citation

  • Bo H. Lindqvist & Bjarte Rannestad, 2011. "Monte Carlo exact goodness‐of‐fit tests for nonhomogeneous Poisson processes," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 27(3), pages 329-341, May.
    • Handle: RePEc:wly:apsmbi:v:27:y:2011:i:3:p:329-341
    DOI: 10.1002/asmb.841
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