Abstract
In this research paper, the estimation of the unknown parameters for the exponentiated Weibull Poisson distribution using the concept of generalized order statistics is investigated from Bayesian approach. The squared error, LINEX and general entropy loss functions are considered for Bayesian computation. Bayes estimates based on Progressively type II censored and the joint density function of ordinary order statistics are considered as special cases of generalized order statistics. Finally simulation study is conducted for illustrative purposes.
Highlights
Order statistics and record values play an important role in statistics and its applications in reliability theory and life testing
Bayes estimates based on Progressively type II censored and the joint density function of ordinary order statistics are considered as special cases of generalized order statistics
Step 3: Numerical technique is applied for solving Equations (7), (8) and (9) for the unknown parameters to obtain the Bayesian estimators under squared error, Linear exponential (LINEX) and general entropy loss functions based on generalized order statistics (GOS)
Summary
Order statistics and record values play an important role in statistics and its applications in reliability theory and life testing. Estimated the parameters of the Burr type XII distribution based on GOS and upper record statistics using maximum likelihood (ML), Bayesian and approximate Bayes due to Lindley [20] methods. AbdElfattah, et al [1] obtained maximum likelihood estimators and confidence intervals of the unknown parameters from exponentiated Weibull Poisson (EWP) distribution based on GOS. This was done under assumption of symmetric (square error) and asymmetric (LINEX and general entropy) loss functions.
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