Inference for Kumaraswamy distribution based on type I progressive hybrid censoring
學年 111
學期 1
出版（發表）日期 2022-12-01
作品名稱 Inference for Kumaraswamy distribution based on type I progressive hybrid censoring
作品名稱（其他語言）
著者 Farha Sultana; Yogesh Mani Tripathi; Shuo-Jye Wu; Tanmay Sen
單位
出版者
著錄名稱、卷期、頁數 Annals of Data Science 9(6), p.1283-1307
摘要 In this paper, we investigate the estimation problems of unknown parameters of the Kumaraswamy distribution under type I progressive hybrid censoring. This censoring scheme is a combination of progressive type I and hybrid censoring schemes. We derive the maximum likelihood estimates of parameters using an expectation-maximization algorithm. Bayes estimates are obtained under different loss functions using the Lindley method and importance sampling procedure. The highest posterior density intervals of unknown parameters are constructed as well. We also obtain prediction estimates and prediction intervals for censored observations. A Monte Carlo simulation study is performed to compare proposed methods and one real data set is analyzed for illustrative purposes.
關鍵字 Bayes estimates;Importance sampling;Lindley approximation;Maximum likelihood estimates;One-sample prediction
語言 en
ISSN 2198-5804;2198-5812
期刊性質 國外
收錄於 Scopus
產學合作
通訊作者 Yogesh Mani Tripathi
審稿制度 是
國別 DEU
公開徵稿
出版型式 ,電子版,紙本
SDGS 產業創新與基礎設施