Parameters Estimation for the Exponentiated Weibull Distribution Based on Generalized Progressive Hybrid Censoring Schemes

Ahmed Elshahhat^1,

¹Department of Accounting & Quantitative Information Systems, Faculty of Technology & Development, Zagazig University, Egypt

Cite this paper:
Ahmed Elshahhat. Parameters Estimation for the Exponentiated Weibull Distribution Based on Generalized Progressive Hybrid Censoring Schemes. American Journal of Applied Mathematics and Statistics. 2017; 5(2):33-48. doi: 10.12691/ajams-5-2-1

Abstract

Based on Type-I and Type-II generalized progressive hybrid censoring schemes, the maximum likelihood estimators and Bayes estimators for the unknown parameters of exponentiated Weibull lifetime model are derived. The approximate asymptotic variance-covariance matrix and approximate confidence intervals based on the asymptotic normality of the classical estimators are obtained. Independent non-informative types of priors are considered for the unknown parameters to develop the Bayes estimators and corresponding Bayes risks under a squared error loss function. Proposed estimators cannot be expressed in closed forms and can be evaluated numerically by some suitable iterative procedure. Finally, one real data set is analyzed for illustrative purposes.

Keywords:
asymptotic variance-covariance matrix Bayes estimator confidence interval exponentiated Weibull distribution generalized progressive hybrid censoring schemes maximum likelihood estimator squared error loss function

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