On goodness-of-fit testing for Burr type X distribution under progressively type-II censoring
| Autor: | Ayman Baklizi, Reza Pakyari |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
Statistics and Probability
Cumulative hazard function Computational Mathematics Correlation coefficient Nelson-Aalen estimate Goodness-of-fit testing Progressive Type-II censoring Kalpan–Meier estimate Exponential distribution Statistics Probability and Uncertainty Monte Carlo simulation Burr distribution |
| Zdroj: | Computational Statistics. 37:2249-2265 |
| ISSN: | 1613-9658 0943-4062 |
| DOI: | 10.1007/s00180-022-01197-5 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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