The present article addresses the effects of measurement errors on the estimation of population coefficient of variation C Y of the study variable Y. Bias and mean squared error (MSE) of the proposed estimator are derived upto the first order of approximation under simple random sampling design. A theoretical efficiency comparison is made between the proposed estimator and the usual coefficient of variation estimator in presence of measurement errors. Based on large sample approximations the optimal condition is obtained under which the proposed estimator performs better than the conventional estimator in presence of measurement errors. Theoretical results are verified by the simulation study using R software.
In this paper, we used maximum likelihood and Bayes method to estimate parameter of Rayleigh distribution for right censored survival data type II to know the best method. The prior knowledge which used in Bayes method is Invers Gamma prior. Maximum likelihood and Bayes method under Square Error Loss Function will be compared. We compare these methods by Mean Squared Error (MSE) value using R program. After that, the result will be displayed in tables to facilitate the comparisons.
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