On the Performance of Principal Component Liu-Type Estimator under the Mean Square Error Criterion

Abstract EN

Wu (2013) proposed an estimator, principal component Liu-type estimator, to overcome multicollinearity.

This estimator is a general estimator which includes ordinary least squares estimator, principal component regression estimator, ridge estimator, Liu estimator, Liu-type estimator, r-k class estimator, and r-d class estimator.

In this paper, firstly we use a new method to propose the principal component Liu-type estimator; then we study the superior of the new estimator by using the scalar mean squares error criterion.

Finally, we give a numerical example to show the theoretical results.