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Activity Number: 707
Type: Contributed
Date/Time: Thursday, August 4, 2016 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #319233 View Presentation
Title: Bayesian Estimators of the Odd Weibull Distribution with Censored Data
Author(s): Chin-I Cheng* and Kahadawala Cooray
Companies: and Central Michigan University
Keywords: Adaptive Rejection Sampling ; Adaptive Rejection Metropolis Sampling ; Bayesian Estimate ; Jeffreys prior ; Odd Weibull distribution

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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