On the Maximum Likelihood and Least Squares Estimation for the Inverse Weibull Parameters with Progressively First-Failure Censoring

DOI: 10.4236/ojs.2015.51010   PDF   HTML     3,528 Downloads   5,171 Views   Citations

Abstract

In this article, we consider a new life test scheme called a progressively first-failure censoring scheme introduced by Wu and Kus [1]. 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 are 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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Helu, A. (2015) On the Maximum Likelihood and Least Squares Estimation for the Inverse Weibull Parameters with Progressively First-Failure Censoring. Open Journal of Statistics, 5, 75-89. doi: 10.4236/ojs.2015.51010.

Conflicts of Interest

The authors declare no conflicts of interest.

References

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