Bayesian inference for the parameters of the generalized logistic distribution under a combined framework of generalized type-I and type-II hybrid censoring schemes with application to physical data

Bayesian inference for the parameters of the generalized logistic distribution under a combined framework of generalized type-I and type-II hybrid censoring schemes with application to physical data

This study focuses on the Bayesian inference of parameters for the generalized logistic distribution, utilizing a combined framework of generalized type-I and type-II hybrid censoring schemes. The research addresses limitations in existing censoring methods by proposing a flexible model that enhance...

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Bibliographic Details
Main Authors: Mustafa M. Hasaballah, Oluwafemi Samson Balogun, M. E. Bakr
Format: Article
Language:English
Published: AIP Publishing LLC 2025-01-01
Series:AIP Advances
Online Access:http://dx.doi.org/10.1063/5.0249742
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