A New Generalization of Power Function Distribution: Properties and Estimation Based on Censored Samples

  • Amal S. Hassan Department of Mathematical Statistics, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza, Egypt
  • Said G. Nassr Faculty of Business Administration, Sinai University, Sinai, Egypt
Keywords: Exponentiated generalized power function distribution, moments, order statistics, maximum likelihood estimation


A new four-parameter power function distribution, named as exponentiated generalized power function (EGPF) is proposed. Some of its statistical properties are obtained including moments, probability weighted moments, incomplete moments and Rényi entropy measure. The estimation of the model parameters is performed based on type II censored samples. The maximum likelihood estimators are developed for estimating the model parameters. Asymptotic confidence interval estimators of the model parameters are developed. Simulation procedure and real data are performed to illustrate the theoretical purposes.


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