Minimum mean squared estimation of location and scale parameters under misspecification of the model
模型误设下位置与尺度参数的最小均方距离估计
SUMMARY The paper is concerned with estimating location and scale parameters by estimators minimizing a mean squared distance between the empirical distribution function and a conveniently chosen parameterized-distribution function. Within the true parametric family the location estimator has the same asymptotic distribution as that of Hodges & Lehmann. If the underlying distribution is not a member of the assumed parametric family, the questions concerning bias, rather than…