Sample Design and Estimation of Parameters of Half Logistic Distribution Using Generalized Ranked-Set Sampling

Abstract

The ranked-set sampling technique has been generalized so that a more efficient estimator may be obtained. This technique allows more than one unit from each set to be quantified. Consequently, the number of units to be sampled may be reduced significantly and as a result, the corresponding cost would also be reduced. The generalized ranked-set sampling technique is applied in the estimation of parameters of the half logistic distribution. New estimators are proposed which include linear minimum variance unbiased estimators and ranked-set sample estimators. The coefficients, variances and relative efficiencies are tabulated. The estimators are compared to the best linear unbiased estimator of the parameters. Sample design strategy is also considered.