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Abstract

In this paper we develop approximate Bayes estimators of the parameters,
reliability, and hazard rate functions of the Logistic distribution by using Lindley’s
approximation, based on progressively type-II censoring samples. Noninformative
prior distributions are used for the parameters. Quadratic, linex
and general Entropy loss functions are used. The statistical performances of the
Bayes estimates relative to quadratic, linex and general entropy loss functions
are compared to those of the maximum likelihood based on simulation study.

Keywords

Logistic distribution progressively type-II censoring linex and general Entropy loss functions Lindley’s Bayes approximation

Article Details

Author Biographies

Mohamed Mahmoud Mohamed, Professor, Department of Mathematics, Faculty of Science, Ain Shams University, Cairo, Egypt

Professor, Department of Mathematics, Faculty of Science, Ain Shams University, Cairo, Egypt

Ahmed Rashad Moussa, Professor, Department of Mathematics, Faculty of Science, Helwan University, Ain Helwan, Cairo, Egypt.

Professor, Department of Mathematics, Faculty of Science, Helwan University, Ain Helwan, Cairo, Egypt.

Mohammed Yusuf Abdelaziz, Assistant Lecturer, Department of Mathematics, Faculty of Science, Helwan University, Ain Helwan, Cairo, Egypt.

Assistant Lecturer,

Department of Mathematics, Faculty of Science, Helwan University, Ain Helwan, Cairo, Egypt.
How to Cite
Mohamed, M. M., Moussa, A. R., & Abdelaziz, M. Y. (2016). Approximate Bayes Estimators of the Logistic Distribution Parameters Based on Progressive Type-II Censoring Scheme. Pakistan Journal of Statistics and Operation Research, 12(3), 519-531. https://doi.org/10.18187/pjsor.v12i3.1176