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On the Anderson–Darling Type Test for Inhomogeneous Poisson Processes

Ali S. Dabye et al.

Mathematical Methods of Statistics2025https://doi.org/10.3103/s1066530725700061article
ABDC B
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0.37

What the paper says

This paper addresses the construction of the Anderson–Darling goodness-of-fit (GoF) test for inhomogeneous Poisson processes. We begin by considering simple basic hypotheses with a non-parametric alternative. It is demonstrated that the test based on this statistic is asymptotically distribution-free (ADF). Subsequently, we assume that the mean intensity function of the process under the null hypothesis follows a parametric form with an unknown shift parameter. The unknown parameter is estimated using the maximum likelihood estimator, and it is shown that in this case, the limiting distribution of the test statistic does not depend on the true value of this parameter.

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https://doi.org/https://doi.org/10.3103/s1066530725700061

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@article{ali2025,
  title        = {{On the Anderson–Darling Type Test for Inhomogeneous Poisson Processes}},
  author       = {Ali S. Dabye et al.},
  journal      = {Mathematical Methods of Statistics},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.3103/s1066530725700061},
}

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On the Anderson–Darling Type Test for Inhomogeneous Poisson Processes

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.