左截断右删失数据下指数分布参数多变点的贝叶斯估计
좌절단우산실수거하지수분포삼수다변점적패협사고계
On Bayesian Estimation of Parameter of Exponential Distribution with Multiple Change Points for Randomly Truncated and Censored Data
  • 万方数据
    西南师范大学学报（自然科学版） 서남사범대학학보（자연과학판）
    JOURNAL OF SOUTHWEST CHINA NORMAL UNIVERSITY
    2015年 1期 12-17 ,共6页

    何朝兵%刘跃军%刘华文

    하조병%류약군%류화문

    完全数据似然函数%满条件分布%MCMC方法%Gibbs抽样%Metropolis-Hastings算法 完全數據似然函數%滿條件分佈%MCMC方法%Gibbs抽樣%Metropolis-Hastings算法
    완전수거사연함수%만조건분포%MCMC방법%Gibbs추양%Metropolis-Hastings산법
    complete-data likelihood function%full conditional distribution%MCMC method%Gibbs sam-pling%Metropolis-Hastings algorithm
    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。
    주요이용MCMC방법연구료좌절단우산실수거하지수분포다변점모형적삼수고계문제。통과사선법화역변환법득도료지수분포적완전수거，재획득각삼수적만조건분포후，이용MCMC방법득도료Gibbs양본，파Gibbs양본적균치작위각삼수적고계。수궤모의적결과표명각삼수고계적정도도교고。
    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 .
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