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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/10749

Title: Analysis of Progressive Censoring Competing Risks Data with Binomial Removals
Authors: . Sarhan, Ammar M
I. Al-Wasel
M. Alameri
Keywords: Maximum likelihood estimator
variance covariance matrix, goodness of fit
Issue Date: 2008
Publisher: Int. Journal of Math. Analysis,
Citation: Vol. 2, 2008, no. 20, 965 - 976
Abstract: In several studies in reliability and in medical science, the cause of failure/death of items or individuals may be attributable to more then one cause. In this paper, we will study the competing risks model when the data is progressively Type-II censored with random removals. We study the model under the assumption of independent causes of failure and exponential lifetimes, where the number of items or individuals removed at each failure time follows binomial distribution. The maximum likelihood estimators of the unknown parameters included in the model and their asymptotic distributions are derived. A set of real data is provided for illustrative purpose.
URI: http://hdl.handle.net/123456789/10749
Appears in Collections:College of Science

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