Consider the problem of estimating a $p{ imes}1$ mean vector ${underline{ heta}}(p{geq}4)$ under the quadratic loss, based on a sample ${underline{x}_{1}},;{cdots}{underline{x}_{n}}$. We find an optimal decision rule within the class of Lindley type decision rules which shrink the usual one toward the mean of observations when the underlying distribution is that of a variance mixture of normals and when the norm ${parallel};{underline{ heta}};-;{ar{ heta}}{underline{1}};{parallel}$ is known, where ${ar{ heta}}=(1/p){sum_{i=1}^p}{ heta}_i$ and $underline{1}$ is the column vector of ones.