Bayesian Estimation for Generalized Exponential Distribution Based on Progressive Type-I Interval Censoring  

作　　者：Xiu-yun PENG Zai-zai YAN 

机构地区：[1]Science College, Inner Mongolia University of Technology

出　　处：《Acta Mathematicae Applicatae Sinica》2013年第2期391-402,共12页应用数学学报（英文版）

基　　金：Supported by the National Natural Science Foundation of China (No. 11161031);Natural Science Foundation of Inner Mongolia (2010MS0116);Higher school science and technology research project of Inner Mongolia (NJ10085)

摘　　要：In this study, we consider the Bayesian estimation of unknown parameters and reliability function of the generalized exponential distribution based on progressive type-I interval censoring. The Bayesian estimates of parameters and reliability function cannot be obtained as explicit forms by applying squared error loss and Linex loss functions, respectively; thus, we present the Lindley＇s approximation to discuss these estimations. Then, the Bayesian estimates are compared with the maximum likelihood estimates by using the Monte Carlo simulations.In this study, we consider the Bayesian estimation of unknown parameters and reliability function of the generalized exponential distribution based on progressive type-I interval censoring. The Bayesian estimates of parameters and reliability function cannot be obtained as explicit forms by applying squared error loss and Linex loss functions, respectively; thus, we present the Lindley＇s approximation to discuss these estimations. Then, the Bayesian estimates are compared with the maximum likelihood estimates by using the Monte Carlo simulations.

关 键 词：Bayesian inference Lindley＇s approximation Monte Carlo method 

分 类 号：O212.8[理学—概率论与数理统计]