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Magdy Nagy Ahmed Ramadan

Assistant Professor

Faculty member

كلية العلوم
College of Science, Building 4, Office 2B-28
publication
Thesis
2017

Statistical Inference for Pareto Distribution based on Progressive Type-I Hybrid Censoring Scheme

Nagy, Magdy . 2017

In this paper, the maximum likelihood and Bayesian estimations are developed based on progressive Type-I hybrid censored sample from the Pareto distribution. The Bayesian estimators for the unknown parameters are computed using the squared error loss function. Also, the point and interval Bayesian predictions for the unobserved failures from the same sample and that from the future sample are derived. Moreover, a Monte Carlo simulation study is carried out to compare the performance of the maximum likelihood and the Bayesian estimators. Finally, numerical example is presented for illustrating all the inferential procedures developed here.
 

more of publication
publications

The procedure of selecting the values of hyper-parameters for prior distributions in Bayesian estimate has produced many problems and has drawn the attention of many authors, therefore the…

by M. Nagy1, M. H. Abu-Moussa, Adel Fahad Alrasheedi and A. Rabie
2022
Published in:
aimspress
publications

By observing the failure behavior of the recorded survival data, we aim to compare the different processing approaches or the effectiveness of the devices or systems applied in this nonparametric…

by M. E. Bakr, M. Nagy and Abdulhakim A. Al-Babtain
2022
Published in:
aimspress