In this paper, The problem of estimating unknown paramaters of Lomax distribution is considered under the assumption that samples are type-II censoring. The maximum likelihood estimates are developed for unknown paramaters using EM algorithm and NR method. We obtain the observed Fisher information matrix using the missing information principle . A numerical study is performed to compare the proposed estimate.
Mixed exponential distribution is a very important statistical model in life data analysis. In this paper, we give Bayesian estimations of mixed exponential distribution with Type-Ⅰ censored data by using conjugate prior distribution based on square loss function. And we prove that the Bayesian estimations are admissible.
We discuss the empirical Bayesian estimation and the noninformative prior Bayesian estimation of Exponential parameter in the missing data occasion. By setting different prior distributions, we get different bayesian risks and compare the numerical simulation results through the MATLAB programming.
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