Bayes inference using half-logistic generated Weibull model based on type-II censoring

Essam K. AL-Hussaini and Alaa H. Abdel-Hamid

Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 5, 2103-2122

Abstract: A new distribution, called half-logistic generated Weibull distribution (HLGWD), is obtained by composing a half-logistic cumulative distribution function H with a function η(x)=-lnG(x)$\eta (x)=-\text{ln }G(x)$, where G(x) is Weibull, such that H(η(x)) is a survival function. Some properties of the new distribution are presented. A real data set is analyzed using the generated class of distributions which shows that the HLGWD can be used quite effectively in analyzing real lifetime data. Bayes estimation and one-sample Bayes prediction of future observables from the HLGWD are obtained and computed.

Date: 2017
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DOI: 10.1080/03610926.2015.1032427

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