Progressive First-Failure Censored Samples in Estimation and Prediction of NH Distribution

2022 ◽  
Vol 11 (1) ◽  
pp. 189-204
Keyword(s):  
Estimation And Prediction ◽  
Censored Samples

scholarly journals Bayesian Estimation and Prediction Based on Progressively First Failure Censored Scheme from a Mixture of Weibull and Lomax Distributions

2020 ◽  
pp. 357-372
Author(s):  
Mohamed M. Mahmoud ◽  
Manal Mohamed Nassar ◽  
Marwa Ahmed Aefa
Keyword(s):  
Monte Carlo ◽  
Maximum Likelihood ◽  
Bayesian Estimation ◽  
Likelihood Estimation ◽  
Bayes Estimation ◽  
Maximum Likelihood Estimates ◽  
Monte Carlo Simulation Study ◽  
Estimation And Prediction ◽  
Censored Samples ◽  
Symmetric Square

This paper develops Bayesian estimation and prediction, for a mixture of Weibull and Lomax distributions, in the context of the new life test plan called progressive first failure censored samples. Maximum likelihood  estimation and Bayes estimation, under informative and non-informative priors, are obtained using Markov Chain Monte Carlo methods, based on the symmetric square error Loss function and the asymmetric linear exponential (LINEX) and general entropy loss functions. The maximum likelihood estimates and the different Bayes estimates are compared via a Monte Carlo simulation study. Finally, Bayesian prediction intervals for future observations are obtained using a numerical example

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