Order Statistical and Censored Data For Weibull Lindley Rayleigh Distribution

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Hind Adnan , et. al

Abstract

In this paper, we study statistical inferences on the maximum likelihood estimation of the Weibull Lindley Rayleigh distribution when data are randomly censored. Likelihood equations are derived assuming that the censoring distribution does not involve any parameters of interest. The maximum likelihood estimators (MLEs) of the censored the Weibull Lindley Rayleigh distribution do not have an explicit form, and it should be solved in an iterative way. By using the same method, the observed Fisher information is also approximated to obtain asymptotic variances of the estimators. An illustrative example is presented, and a simulation study is conducted to compare the performances of the estimators. In addition to their explicit form, the approximate MLEs are as efficient as the MLEs in terms of variances.

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