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Approximate maximum likelihood estimation of the mean and standard deviation of the normal distribution based on type ii censored samples
Abstract:It is known that the maximum likelihood methods does not provide explicit estimators for the mean and standard deviation of the normal distribution based on Type II censored samples. In this paper we present a simple method of deriving explicit estimators by approximating the likelihood equations appropriately. We obtain the variances and covariance of these estimators. We also show that these estimators are almost as eficient as the maximum likelihood (ML) estimators and just as eficient as the best linear unbiased (BLU), and the modified maximum likelihood (MML) estimators. Finally, we illustrate this method of estimation by applying it to Gupta's and Darwin's data.
Keywords:Order statistics  maximum likelihood estimator  Type II censored sample  best linear unbiased estimator  bias  variance  mean square error  robustness
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