Statistics, Department of
The R Journal
Date of this Version
12-2018
Document Type
Article
Citation
The R Journal (December 2018) 10(2); Editor: John Verzani
Abstract
The ridge regression estimator, one of the commonly used alternatives to the conventional ordinary least squares estimator, avoids the adverse effects in the situations when there exists some considerable degree of multicollinearity among the regressors. There are many software packages available for estimation of ridge regression coefficients. However, most of them display limited methods to estimate the ridge biasing parameters without testing procedures. Our developed package, lmridge can be used to estimate ridge coefficients considering a range of different existing biasing parameters, to test these coefficients with more than 25 ridge related statistics, and to present different graphical displays of these statistics.
Included in
Numerical Analysis and Scientific Computing Commons, Programming Languages and Compilers Commons
Comments
Copyright 2018, The R Foundation. Open access material. License: CC BY 4.0 International