A Review on the Biasing Parameters of Ridge Regression Estimator in LRM

Madhulika Dube; Isha

doi:10.15415/mjis.2014.31007

Authors

Madhulika Dube Professor & Head Department of Statistics, M. D. University, Rohtak
Isha Research Scholar Department of Statistics M. D. University, Rohtak

DOI:

https://doi.org/10.15415/mjis.2014.31007

Keywords:

Ordinary Least Squares Estimator, Multicollinearity, Ridge Regression, Biasing Parameter, Ridge Parameters

Abstract

Ridge regression is one of the most widely used biased estimators in the presence of multicollinearity, preferred over unbiased ones since they have a larger probability of being closer to the true parametric value. Being the modification of the least squares method it introduces a biasing parameter to reduce the length of the parameter under study. As these biasing parameters depend upon the unknown quantities, extensive work has been carried out by several authors to work out the best one. Owing to the fact that over the years large numbers of biasing parameters have been proposed and studied, this article presents an annotated bibliography along with the review on various biasing parameter available.

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