Expectation-Maximization Algorithms for Obtaining Estimations of Generalized Failure Intensity Parameters

被引：0

作者：

Krit, Makram ^{[1
]}

Mili, Khaled ^{[1
]}

机构：

[1] Univ Gafsa, Higher Inst Co Adm, Gafsa, Tunisia

来源：

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS | 2016年 / 7卷 / 01期

关键词：

Repairable systems reliability; bathtub failure intensity; EM algorithm; estimation; likelihood; Monte Carlo simulation;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper presents several iterative methods based on Stochastic Expectation-Maximization (EM) methodology in order to estimate parametric reliability models for randomly lifetime data. The methodology is related to Maximum Likelihood Estimates (MLE) in the case of missing data. A bathtub form of failure intensity formulation of a repairable system reliability is presented where the estimation of its parameters is considered through EM algorithm. Field of failures data from industrial site are used to fit the model. Finally, the interval estimation basing on large-sample in literature is discussed and the examination of the actual coverage probabilities of these confidence intervals is presented using Monte Carlo simulation method.

引用

页码：432 / 435

页数：4

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