Modified Liu estimators in the linear regression model: An application to Tobacco data.

ABSTRACT:

Background

The problem of multicollinearity in multiple linear regression models arises when the predictor variables are correlated among each other. The variance of the ordinary least squared estimator become unstable in such situation. In order to mitigate the problem of multicollinearity, Liu regression is widely used as a biased method of estimation with shrinkage parameter 'd'. The optimal value of shrinkage parameter plays a vital role in bias-variance trade-off.

Limitation

Several estimators are available in literature for the estimation of shrinkage parameter. But the existing estimators do not perform well in terms of smaller mean squared error when the problem of multicollinearity is high or severe.

Methodology

In this paper, some new estimators for the shri

SUBMITTER: Babar I 

PROVIDER: S-EPMC8608338 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature