Abstract Details
Activity Number:
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490
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Type:
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Contributed
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Date/Time:
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Wednesday, August 12, 2015 : 8:30 AM to 10:20 AM
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Sponsor:
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IMS
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Abstract #314707
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View Presentation
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Title:
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The Inverse Weibull Distribution as a Failure Model Under Various Loss Functions and Based on Progressive First-Failure Censored Data
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Author(s):
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Amal Helu* and Hani Samawi
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Companies:
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Carnegie Mellon University Qatar and Georgia Southern University
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Keywords:
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inverse Weibull distribution ;
Lindley's approximation ;
progressive first-failure censoring ;
maximum likelihood
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Abstract:
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We consider statistical inferences about the unknown parameters of the inverse Weibull distribution based on progressively first-failure censoring using Bayesian procedures. The Bayes estimators are obtained based on both the symmetric and asymmetric (Linex, General Entropy and Precautionary) loss functions. There are no explicit forms for the Bayes estimators; therefore, we propose the Lindley's approximation method to compute the Bayes estimators. A comparison between these estimators and the maximum likelihood estimator (MLE) is provided by using extensive simulation and two criteria, namely, the bias and the mean squared error. It is concluded that the approximate Bayes estimators outperform the MLEs most of the time. Real life data example is provided to illustrate our proposed estimators.
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Authors who are presenting talks have a * after their name.
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