# James-Stein Estimator

From Open Risk Manual

## 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