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Activity Number: 189
Type: Contributed
Date/Time: Monday, August 1, 2016 : 10:30 AM to 12:20 PM
Sponsor: International Indian Statistical Association
Abstract #320549
Title: On the Maximum Likelihood and Least Squares Estimation for the Inverse Weibull Parameters with Progressively First-Failure Censoring
Author(s): Amal Helu*
Companies: Carnegie Mellon University
Keywords: progressive first-failure censoring ; maximum likelihood ; least squares method
Abstract:

In this article we consider a new life test scheme called a progressively first-failure censoring scheme introduced by Wu and Kus . Based on this type of censoring, the maximum likelihood, approximate maximum likelihood and the least squares method estimators for the unknown parameters of the inverse Weibull distribution are derived. A comparison between these estimators is provided by using extensive simulation and two criteria, namely, absolute bias and mean squared error. It is concluded that the estimators based on the least squares method is superior compared to the maximum likelihood and the approximate maximum likelihood estimators. Real life data example is provided to illustrate our proposed estimators.


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