European Journal of Statistics and Probability (EJSP)

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Maximum Likelihood Estimator

Bayesian Estimation of the Parameters of the Exponentiated Weibull Distribution with Progressively Type I Inteval Censored Sample (Published)

In this paper, Bayes, investigation the unknown shape Parameters, of the exponentiated Weibull life time model (EWD) are derived from progressive type I interval censored samples using different loss functions and independent and dependent conjugate priors. Besides, the maximum likelihood estimators have also been attempted. Approximate Credible and Shortest Credible intervals for the parameters of an EWD are obtained.  A numerical illustration for these new results is also given.

Keywords: Bayes Estimator, Exponentiated Weibull distribution, Informative Prior, Maximum Likelihood Estimator, Non-informative prior

An Empirical Study on Modified Maximum Likelihood Estimator and Maximum Likelihood Estimator for Inverse Weibull Distribution by Using Type Ii Censored Sample (Review Completed - Accepted)

Parameter estimation become complicated when censoring is present in the sample Some time it is not possible to give a mathematical expression of estimated values of parameters in Maximum Likelihood (ML) method. .Dayyeh and Sawi (1996) used the Mehrotra and Nanda (1974) MML technique. They replaced the intractable term of likelihood equations with its expectation, to get the estimators of location parameter by considering the scale parameter equal to 1 of logistic distribution in right Type ll censored sample. Kambo (1978) derived the explicit solution for ML estimator of two parameter exponential distribution in the case of doubly type ll censored sample. In this paper MML estimator and ML estimator of inverse weibull distribution by using type II censored sample have been derived and compared in term of asymptotic variances and mean square error. The purpose of conducting the empirical study is to study the closeness of MML estimators to ML estimator, and relative efficiency of censored sample to complete sample.

Keywords: Asymptotic Variances, Bias, Inverse weibull distribution Order Statistics, Maximum Likelihood Estimator, Mean Square Error, Modified Maximum Likelihood Estimator, Type II censored sample

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