ESTIMASI PARAMETER DISTRIBUSI RAYLEIGH MENGGUNAKAN METODE MINIMAX DENGAN FUNGSI KERUGIAN KUADRATIK DAN EKSPONENSIAL LINIER TERMODIFIKASI - , RADHIATUR RAHMI ([Yogyakarta] : Universitas Gadjah Mada, 2013)
The minimax estimation is an upgraded non-clasical approach method in the estimation area of statistical inference which is closely related with Bayes estimation. The most important element in this estimation are the prior distribution and the loss function. In the thesis, parameter estimation of the Rayleigh distribution using minimax estimation method under quadratic and modified linier exponential loss function is studied. The prior distribution as used in this estimation is invers moment prior distribution. In the data simulation, the estimated values of the parameter and mean squared error (MSE) of the estimators are computed. And the result indicate that for small sample size (n < 25) dan c in interval (-2,3), semi minimax estimator under modified linier exponential loss function appear to be better (efficient) than the semi minimax estimator under quadratic loss function. But for sample size (n < 25) and other c show the opposite result. And for large sample size (n > 25), both of estimators have approximately the same mean squared error (MSE).