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New goodness of fit tests for the Pareto distribution using Stein’s characterization for uncensored and random right censored data

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  • Deepesh Bhati
  • Apostolos Batsidis
  • Sakshi Khandelwal

Abstract

Based on Stein’s method, we propose a new test for the Pareto type I distribution. The proposed test, initially defined for the full sample case, is appropriately modified in order to deal with randomly right-censored observations. The finite-sample performance of the new tests is numerically assessed through an extensive simulation experiment, including comparisons with other existing tests. In many cases, the novel tests either outperform or match the performance of existing ones. Real data applications, including uncensored and censored data, are considered for illustrative purposes.

Suggested Citation

  • Deepesh Bhati & Apostolos Batsidis & Sakshi Khandelwal, 2025. "New goodness of fit tests for the Pareto distribution using Stein’s characterization for uncensored and random right censored data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 54(24), pages 7865-7889, December.
    • Handle: RePEc:taf:lstaxx:v:54:y:2025:i:24:p:7865-7889
    DOI: 10.1080/03610926.2025.2483973
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