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has been cited by the following article:

• TITLE: Estimation Based on Progressive First-Failure Censored Sampling with Binomial Removals

  AUTHORS: Ahmed A. Soliman, Ahmed H. Abd Ellah, Nasser A. Abou-Elheggag, Rashad M. El-Sagheer

  KEYWORDS: Burr-X Distribution; Progressive First-Failure Censored; Bayesian and Non-Bayesian Estimations; Loss Function; Bootstrap; Random Removals

  JOURNAL NAME: Intelligent Information Management, Vol.5 No.4, July 17, 2013

  ABSTRACT: In this paper, the inference for the Burr-X model under progressively first-failure censoring scheme is discussed. Based on this new censoring were the number of units removed at each failure time has a discrete binomial distribution. The maximum likelihood, Bootstrap and Bayes estimates for the Burr-X distribution are obtained. The Bayes estimators are obtained using both the symmetric and asymmetric loss functions. Approximate confidence interval and highest posterior density interval (HPDI) are discussed. A numerical example is provided to illustrate the proposed estimation methods developed here. The maximum likelihood and the different Bayes estimates are compared via a Monte Carlo simulation study.