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has been cited by the following article:

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

  AUTHORS: Amal Helu

  KEYWORDS: Inverse Weibull Distribution, Progressive First-Failure Censoring, Maximum Likelihood, Least Squares Method

  JOURNAL NAME: Open Journal of Statistics, Vol.5 No.1, February 26, 2015

  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.