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On goodness-of-fit testing for Burr type X distribution under progressively type-II censoring

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Abstract

In this article, we propose two goodness-of-fit test statistics for the Burr Type X distribution when the available data are subject to progressively Type-II censoring. The proposed test statistics are based on the sample correlation coefficient between the Kaplan-Meier estimator of the survival function and the lifetime data and also based on the correlation between the Nelson-Aalen estimator of the cumulative hazard function and the lifetime data. The new tests exhibit good performance in terms of power in compare to the EDF-based test statistics of Pakyari and Balakrishnan (IEEE Trans Reliab 61:238–242, 2012). The maximum likelihood estimator of the unknown Burr Type X model is also studied and an approximate estimator is given. Finally, two real datasets are analyzed for illustrative purposes.

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Acknowledgements

We are grateful to the associate editor and anonymous reviewers for their careful reading and providing most helpful comments and suggestions on an earlier draft which led to this improved version of the paper.

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Authors and Affiliations

  1. Statistics Program, Department of Mathematics, Statistics and Physics, College of Arts and Sciences, Qatar University, 2713, Doha, Qatar

    Reza Pakyari & Ayman Baklizi

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  1. Reza Pakyari
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  2. Ayman Baklizi
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Correspondence to Reza Pakyari.

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Pakyari, R., Baklizi, A. On goodness-of-fit testing for Burr type X distribution under progressively type-II censoring. Comput Stat 37, 2249–2265 (2022). https://doi.org/10.1007/s00180-022-01197-5

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  • DOI: https://doi.org/10.1007/s00180-022-01197-5

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