James-Stein Estimator

Definition

The James–Stein Estimator is a biased estimator of the mean of Gaussian random vectors.

It can be shown that the James–Stein estimator dominates the "ordinary" least squares / maximum likelihood approach, i.e., it has lower mean squared error. It is the best-known example of Stein's phenomenon.

Usage

In practice the implication is that when three or more unrelated parameters are measured, their total MSE can be reduced by using a combined estimator

See Also

• wikipedia entry