POINT ESTIMATION OF THE PARAMETER OF GEOMETRIC DISTRIBUTION UNDER A PARTICULAR RANDOM CENSORING TEST

HE ChaoBing

doi:10.16579/j.issn.1001.9669.2017.01.012

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POINT ESTIMATION OF THE PARAMETER OF GEOMETRIC DISTRIBUTION UNDER A PARTICULAR RANDOM CENSORING TEST

更新时间：2022-09-22

- POINT ESTIMATION OF THE PARAMETER OF GEOMETRIC DISTRIBUTION UNDER A PARTICULAR RANDOM CENSORING TEST
- Journal of Mechanical Strength Vol. 39, Issue 1, Pages: 67-70(2017)
- 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.1001.9669.2017.01.012
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HE ChaoBing. POINT ESTIMATION OF THE PARAMETER OF GEOMETRIC DISTRIBUTION UNDER A PARTICULAR RANDOM CENSORING TEST. [J]. 39(1):67-70(2017)
DOI：

HE ChaoBing. POINT ESTIMATION OF THE PARAMETER OF GEOMETRIC DISTRIBUTION UNDER A PARTICULAR RANDOM CENSORING TEST. [J]. 39(1):67-70(2017) DOI： 10.16579/j.issn.1001.9669.2017.01.012.

摘要

利用极大似然法(ML)和EM算法研究了一类特殊随机截尾试验下几何分布参数的极大似然估计。给出了参数MLE的存在唯一性证明和参数的EM迭代公式。利用Louis算法得到了EM估计的渐近方差.随机模拟的结果表明MLE和EM估计的精度较高,两者的差别非常小。

Abstract

The MLE of geometric distribution are studied by ML method and EM algorithm under a particular random censoring test. The proof of existence and uniqueness of MLE and EM iterative formula of the parameter are given. The asymptotic variance of EM estimation is obtainde by Louis algorithm. Random simulation results show that the MLE and EM estimation are both fairly accurate,and make little difference.

关键词

随机截尾试验几何分布极大似然估计EM算法渐近方差

Keywords

Random censoring testGeometric distributionMaximum likelihood estimationEM algorithmAsymptotic variance

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Department of Statistics,School of Mathematics,Southwest Jiaotong University

School of Mathematics and Physics, Jingchu University of Technology

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