Estimation of dependent competing risks model with baseline proportional hazards models under minimum ranked set sampling
學年 111
學期 2
出版(發表)日期 2023-03-17
作品名稱 Estimation of dependent competing risks model with baseline proportional hazards models under minimum ranked set sampling
作品名稱(其他語言)
著者 Y Zhou, L Wang, T-R Tsai, YM Tripathi
單位
出版者
著錄名稱、卷期、頁數 Mathematics 2023 11(6), 1461
摘要 The ranked set sampling (RSS) is an efficient and flexible sampling method. Based on a modified RSS named minimum ranked set sampling samples (MinRSSU), inference of a dependent competing risks model is proposed in this paper. Then, Marshall–Olkin bivariate distribution model is used to describe the dependence of competing risks. When the competing risks data follow the proportional hazard rate distribution, a dependent competing risks model based on MinRSSU sampling is constructed. In addition, the model parameters and reliability indices were estimated by the classical and Bayesian method. Maximum likelihood estimators and corresponding asymptotic confidence intervals are constructed by using asymptotic theory. In addition, the Bayesian estimator and highest posterior density credible intervals are established under the general prior. Furthermore, according to E-Bayesian theory, the point and interval estimators of model parameters and reliability indices are obtained by a sampling algorithm. Finally, extensive simulation studies and a real-life example are presented for illustrations.
關鍵字 dependent competing risks;bivariate distribution family;maximum likelihood estimation;bayesian estimation;E-Bayesian estimation
語言 en_US
ISSN 2227-7390
期刊性質 國外
收錄於 SCI
產學合作
通訊作者
審稿制度
國別 CHE
公開徵稿
出版型式 ,電子版
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/124285 )