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

Reza Pakyari () and Ayman Baklizi
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Reza Pakyari: Qatar University

Computational Statistics, 2022, vol. 37, issue 5, No 8, 2249-2265

Abstract: 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.

Keywords: Burr distribution; Correlation coefficient; Cumulative hazard function; Exponential distribution; Goodness-of-fit testing; Kalpan–Meier estimate; Nelson-Aalen estimate; Monte Carlo simulation; Progressive Type-II censoring (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s00180-022-01197-5

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