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AuthorPakyari, Reza
AuthorBaklizi, Ayman
Available date2022-01-31T11:10:47Z
Publication Date2022-01-23
Publication NameComputational Statistics
Identifierhttp://dx.doi.org/10.1007/s00180-022-01197-5
CitationPakyari, R., Baklizi, A. On goodness-of-fit testing for Burr type X distribution under progressively type-II censoring. Comput Stat (2022). https://doi.org/10.1007/s00180-022-01197-5
URIhttp://hdl.handle.net/10576/26220
AbstractIn 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.
Languageen
PublisherSpringer
SubjectBurr 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
TitleOn goodness-of-fit testing for Burr type X distribution under progressively type-II censoring
TypeArticle
dc.accessType Abstract Only


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