The concept of uniformly minimum variance unbiased estimation of parameters in statistical inference is undoubtedly an unbeaten criterion to obtain an estimator of an unknown parameter. Often, there are situations where the variability of an estimator is more important and it is possible to obtain an estimator of a parameter which is biased and nonlinear but having lower variability. The concept of shrinkage estimation yields such estimators. The family of James–Stein estimators are the shrinkage estimators which are biased and nonlinear but have smaller variability.