Abstract

A very important distribution called Nakagami distribution is taken into consideration. Reliability measures R(t)=Pr(X>t) and P=Pr(X>Y) are considered. Point as well as interval procedures are obtained for estimation of parameters. Uniformly Minimum Variance Unbiased Estimators (U.M.V.U.Es) and Maximum Likelihood Estimators (M.L.Es) are developed for the said parameters. A new technique of obtaining these estimators is introduced. Moment estimators for the parameters of the distribution have been found. Asymptotic confidence intervals of the parameter based on M.L.E and log(M.L.E) are also constructed. Then, testing procedures for various hypotheses are developed. At the end, Monte Carlo simulation is performed for comparing the results obtained. A real data analysis is performed to describe the procedure clearly.

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