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Activity Number:
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707
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Type:
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Contributed
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Date/Time:
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Thursday, August 4, 2016 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Bayesian Statistical Science
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Abstract #319233
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View Presentation
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Title:
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Bayesian Estimators of the Odd Weibull Distribution with Censored Data
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Author(s):
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Chin-I Cheng* and Kahadawala Cooray
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Companies:
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and Central Michigan University
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Keywords:
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Adaptive Rejection Sampling ;
Adaptive Rejection Metropolis Sampling ;
Bayesian Estimate ;
Jeffreys prior ;
Odd Weibull distribution
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Abstract:
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The Odd Weibull distribution is a three-parameter generalization of the Weibull distribution. The Bayesian methods with Jeffreys priors for estimating parameters of the Odd Weibull with censored data is considered. The Adaptive Rejection Sampling (ARS) and Adaptive Rejection Metropolis Sampling (ARMS) are adapted to generate random samples from full conditionals for inferences on parameters. The estimates based on Bayesian and maximum likelihood on censored data are compared. In order to clarify and advance the validity of Bayesian and likelihood estimators of the Odd Weibull distribution, one simulated data set and two examples about failure time are analyzed.
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Authors who are presenting talks have a * after their name.
