Robust Shrinkage Estimation under Schwartz Space

Robust Shrinkage Estimation under Schwartz Space

In this paper, we are basically discussing on a class of Stein-type shrinkage estimators of the vector parameter in a location model, with errors belonging to a sub-class of elliptically contoured distributions. We derive conditions under Schwartz space in which the underlying class of shrinkage estimators outperforms the sample mean. It is nicely presented that the dominant properties of the class of estimators are robust truly respect to departures from normality.