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

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 , 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.

KEYWORDS AND PHRASES:

• Composition of CDFs
• half-logistic and Weibull distributions
• type-II censoring
• Bayes estimation
• one-sample Bayes prediction
• simulation.

MATHEMATICS SUBJECT CLASSIFICATION:

• 62F10
• 62F15
• 62N01

Acknowledgments

The authors thank the editor and anonymous referees for their suggestions and comments, which significantly improved this manuscript.