Improved Bayesian Inferences for Right-Censored Birnbaum–Saunders Data

This work focuses on making Bayesian inferences for the two-parameter Birnbaum–Saunders (BS) distribution in the presence of right-censored data. A flexible Gibbs sampler is employed to handle the censored BS data in this Bayesian work that relies on Jeffrey’s and Achcar’s reference priors. A compre...

詳細記述

書誌詳細

出版年:	Mathematics
第一著者:	Kalanka P. Jayalath
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2024-03-01
主題:	Bayesian inference censoring Gibbs sampler Jeffrey’s Prior reference prior
オンライン･アクセス:	https://www.mdpi.com/2227-7390/12/6/874