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高校应用数学学报  2015, Vol. 30 Issue (2): 127-138    
    
删失截断情形下Weibull分布多变点模型的参数估计
何朝兵
安阳师范学院 数学与统计学院, 河南安阳 455000
Parameter estimation of Weibull distribution with multiple change points for truncated and censored data
HE Chao-bing
School of Mathematics and Statistics, Anyang Normal University, Anyang 455000, China
 全文: PDF 
摘要: 通过添加缺失的寿命变量数据, 得到了删失截断情形下Weibull分布多变点模型的完全数据似然函数, 研究了变点位置参数和形状参数以及尺度参数的满条件分布. 利用Gibbs抽样与Metropolis-Hastings算法相结合的MCMC方法得到了参数的Gibbs样本, 把Gibbs样本的均值作为各参数的Bayes 估计. 详细介绍了MCMC方法的实施步骤. 随机模拟试验的结果表明各参数Bayes估计的精度都较高.
关键词: 完全数据似然函数满条件分布MCMC方法Gibbs抽样Metropolis-Hastings算法    
Abstract: By filling in the missing data of the life variable, the complete-data likelihood function of Weibull distribution with multiple change points for truncated and censored data is obtained. The full conditional distributions of change-point positions, shape parameters, and scale parameters are studied. Gibbs samples of the parameters are obtaines by MCMC method of Gibbs sampling together with Metropolis-Hastings algorithm, and the means of Gibbs samples are taken as Bayesian estimations of the parameters. The implementation steps of MCMC method are introduced in detail. The random simulation test results show that Bayesian estimations of the parameters are fairly accurate.
Key words: complete-data likelihood function    full conditional distribution    MCMC method    Gibbs sampling    Metropolis-Hastings algorithm
收稿日期: 2014-12-14 出版日期: 2018-06-05
CLC:  O213.2  
基金资助: 国家自然科学基金(61174099); 河南省教育厅科学技术研究重点项目(14B110011)
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引用本文:

何朝兵. 删失截断情形下Weibull分布多变点模型的参数估计[J]. 高校应用数学学报, 2015, 30(2): 127-138.

HE Chao-bing. Parameter estimation of Weibull distribution with multiple change points for truncated and censored data. Applied Mathematics A Journal of Chinese Universities, 2015, 30(2): 127-138.

链接本文:

http://www.zjujournals.com/amjcua/CN/        http://www.zjujournals.com/amjcua/CN/Y2015/V30/I2/127

[1] 何朝兵. 删失截断情形下失效率变点模型的Bayes参数估计[J]. 高校应用数学学报, 2016, 31(4): 413-427.
[2] 程迪, 张世斌. 动态异方差随机前沿模型的Bayesian推断[J]. 高校应用数学学报, 2016, 31(2): 127-135.