左截断右删失数据下指数分布参数多变点的贝叶斯估计

何朝兵,刘跃军,刘华文

doi:10.13718/j.cnki.xsxb.2015.01.003

西南师范大学学报(自然科学版)

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左截断右删失数据下指数分布参数多变点的贝叶斯估计

何朝兵,刘跃军,刘华文. 左截断右删失数据下指数分布参数多变点的贝叶斯估计[J]. 西南师范大学学报(自然科学版), 2015, 40(1). doi: 10.13718/j.cnki.xsxb.2015.01.003

引用本文:

HE Chao-bing,LIU Yue-jun,LIU Hua-wen. On Bayesian Estimation of Parameter of Exponential Distribution with Multiple Change Points for Randomly Truncated and Censored Data[J]. Journal of Southwest China Normal University(Natural Science Edition), 2015, 40(1). doi: 10.13718/j.cnki.xsxb.2015.01.003

Citation:

HE Chao-bing,LIU Yue-jun,LIU Hua-wen. On Bayesian Estimation of Parameter of Exponential Distribution with Multiple Change Points for Randomly Truncated and Censored Data[J]. Journal of Southwest China Normal University(Natural Science Edition), 2015, 40(1). doi: 10.13718/j.cnki.xsxb.2015.01.003

左截断右删失数据下指数分布参数多变点的贝叶斯估计

何朝兵,刘跃军,刘华文

安阳师范学院数学与统计学院,河南安阳,455000 安阳师范学院软件学院,河南安阳,455000 山东大学数学学院,济南,250100

On Bayesian Estimation of Parameter of Exponential Distribution with Multiple Change Points for Randomly Truncated and Censored Data

HE Chao-bing,LIU Yue-jun,LIU Hua-wen

摘要: 主要利用MCMC方法研究了左截断右删失数据下指数分布多变点模型的参数估计问题。通过筛选法和逆变换法得到了指数分布的完全数据，在获得各参数的满条件分布后，利用MCMC方法得到了Gibbs样本，把Gibbs样本的均值作为各参数的估计。随机模拟的结果表明各参数估计的精度都较高。
- 完全数据似然函数 /
- 满条件分布 /
- MCMC方法 /
- Gibbs抽样 /
- Metropolis-Hastings算法
Abstract: Parameter estimation in exponential distribution multiple change points model for randomly trun-cated and censored data has been studied in this paper .The complete data of exponential distribution has been obtained by screening method and inverse transformation method .After the full conditional distribu-tions of all parameters have been obtained ,Gibbs samples have been obtained in MCMC method ,and the means of Gibbs samples has been taken as Bayesian estimations of the parameters .Random simulation re-sults show that Bayesian estimations of the parameters are fairly accurate .
- complete-data likelihood function，full conditional distribution，MCMC method，Gibbs sam-pling，Metropolis-Hastings algorithm /

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左截断右删失数据下指数分布参数多变点的贝叶斯估计

何朝兵,刘跃军,刘华文

安阳师范学院数学与统计学院,河南安阳,455000 安阳师范学院软件学院,河南安阳,455000 山东大学数学学院,济南,250100

关键词:

摘要: 主要利用MCMC方法研究了左截断右删失数据下指数分布多变点模型的参数估计问题。通过筛选法和逆变换法得到了指数分布的完全数据，在获得各参数的满条件分布后，利用MCMC方法得到了Gibbs样本，把Gibbs样本的均值作为各参数的估计。随机模拟的结果表明各参数估计的精度都较高。

English Abstract

On Bayesian Estimation of Parameter of Exponential Distribution with Multiple Change Points for Randomly Truncated and Censored Data

安阳师范学院数学与统计学院,河南安阳,455000 安阳师范学院软件学院,河南安阳,455000 山东大学数学学院,济南,250100

Keywords:

Abstract: Parameter estimation in exponential distribution multiple change points model for randomly trun-cated and censored data has been studied in this paper .The complete data of exponential distribution has been obtained by screening method and inverse transformation method .After the full conditional distribu-tions of all parameters have been obtained ,Gibbs samples have been obtained in MCMC method ,and the means of Gibbs samples has been taken as Bayesian estimations of the parameters .Random simulation re-sults show that Bayesian estimations of the parameters are fairly accurate .