Smoothed Mann–Whitney–Wilcoxon Procedure for Two-Sample Location Problem

Abstract

This study is mainly concerned with estimating a shift parameter in the two-sample location problem. The proposed Smoothed Mann–Whitney–Wilcoxon method smooths the empirical distribution functions of each sample by using convolution technique, and it replaces unknown distribution functions F(x) and G(x − Δ0) with the new smoothed distribution functions F s (x) and G s (x − Δ0), respectively. The unknown shift parameter Δ0 is estimated by solving the gradient function S n (Δ) with respect to an arbitrary variable Δ. The asymptotic properties of the new estimator are established under some conditions that are similar to the Generalized Wilcoxon procedure proposed by Anderson and Hettmansperger (1996). Some of these properties are asymptotic normality, asymptotic level confidence interval, and hypothesis testing for Δ0. Asymptotic relative efficiency of the proposed method with respect to the least squares, Generalized Wilcoxon and Hodges and Lehmann (1963) procedures are also calculated under the contaminated normal model.