Expectation-Maximization Algorithms for Obtaining Estimations of Generalized Failure Intensity Parameters
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 1
Abstract
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.
Authors and Affiliations
Makram KRIT, Khaled MILI
Keywords
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- EP ID EP117663
- DOI 10.14569/IJACSA.2016.070158
- Views 99
- Downloads 0
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