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Digital Object Identifier (DOI) : 10.14569/IJACSA.2016.070158
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 1, 2016.
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.
Makram KRIT and Khaled MILI, “Expectation-Maximization Algorithms for Obtaining Estimations of Generalized Failure Intensity Parameters” International Journal of Advanced Computer Science and Applications(IJACSA), 7(1), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070158