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IIRCT下对数正态分布参数多变点的贝叶斯估计 被引量:1

Bayesian estimation of parameter of lognormal distribution with multiple change points for random censoring test model with incomplete information
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摘要 通过添加缺损的寿命数据,得到了带有不完全信息随机截尾试验下对数正态分布多变点模型的完全数据似然函数.利用MCMC方法对各参数的满条件分布分别进行抽样,详细介绍了MCMC方法的实施步骤.随机模拟试验结果表明各参数贝叶斯估计的精度较高. By filling in the missing data of the life variable , the complete data likelihood function of lognormal distribution with multiple change points for IIRCT is obtained . Every parameter is sampled from its full conditional distribution respectively by MCMC method . The implementation steps of MCMC method are introduced in detail . T he results of random simulation test show that Bayesian estimations of the parameters are fairly accurate .
出处 《西北师范大学学报(自然科学版)》 CAS 北大核心 2015年第5期22-26,共5页 Journal of Northwest Normal University(Natural Science)
基金 国家自然科学基金资助项目(61174099) 河南省教育厅科学技术研究重点项目(14B110011)
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 complete data likelihood function full conditional distribution MCMC method Gibbs sampling Metropolis-Hastings algorithm
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