BAYESIAN ESTIMATION OF GENERALIZED EXPONENTIAL DISTRIBUTION WITH MULTIPLE CHANGE POINTS FOR TRUNCATED AND CENSORED DATA

HE ChaoBing

doi:10.16579/j.issn.1001.9669.2016.02.014

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BAYESIAN ESTIMATION OF GENERALIZED EXPONENTIAL DISTRIBUTION WITH MULTIPLE CHANGE POINTS FOR TRUNCATED AND CENSORED DATA

更新时间：2022-09-22

- BAYESIAN ESTIMATION OF GENERALIZED EXPONENTIAL DISTRIBUTION WITH MULTIPLE CHANGE POINTS FOR TRUNCATED AND CENSORED DATA
- Journal of Mechanical Strength Vol. 38, Issue 2, Pages: 284-287(2016)
- 作者机构：
  
  1. 安阳师范学院数学与统计学院
- 作者简介：
- 基金信息：
- DOI：10.16579/j.issn.1001.9669.2016.02.014
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HE ChaoBing. BAYESIAN ESTIMATION OF GENERALIZED EXPONENTIAL DISTRIBUTION WITH MULTIPLE CHANGE POINTS FOR TRUNCATED AND CENSORED DATA. [J]. 38(2):284-287(2016)
DOI：

HE ChaoBing. BAYESIAN ESTIMATION OF GENERALIZED EXPONENTIAL DISTRIBUTION WITH MULTIPLE CHANGE POINTS FOR TRUNCATED AND CENSORED DATA. [J]. 38(2):284-287(2016) DOI： 10.16579/j.issn.1001.9669.2016.02.014.

摘要

利用筛选法对缺损数据进行了填充,得到了截断删失数据下广义指数分布的完全数据似然函数。利用Gibbs抽样与随机移动Metropolis算法相结合的MCMC方法对各参数进行了抽样。把Gibbs样本的均值作为各参数的估计.随机模拟的结果表明估计的精度较高。

Abstract

The complete-data likelihood function of generalized exponential distribution for truncated and censored data is obtained by filling in the missing data of the life variable using rejection method. All the parameters are sampled by MCMC method of Gibbs sampling together with random-walk Metropolis algorithm. The means of Gibbs samples are taken as the estimations of the parameters. The random simulation test results show that the estimations are fairly accurate.

关键词

完全数据似然函数满条件分布MCMC方法Gibbs抽样随机移动Metropolis算法

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