The R Journal: accepted article

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lmridge: A Comprehensive R Package for the Ridge Regression PDF download
Muhammad Imdad Ullah, Muhammad Aslam and Saima Altaf

Abstract The ridge regression estimator is one of the commonly used alternative to the conventional ordinary least squares estimator that 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 the 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 the 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.

Received: 2018-03-02; online 2018-12-08, supplementary material, (1.6 Kb)
CRAN packages: lmridge, ridge, MASS, lrmest, ltsbase, penalized, glmnet, RXshrink, rrBLUP, RidgeFusion, bigRR, lpridge, genridge, CoxRidge
CRAN Task Views implied by cited CRAN packages: MachineLearning, Survival, Distributions, Econometrics, Environmetrics, Multivariate, NumericalMathematics, Psychometrics, Robust, SocialSciences


CC BY 4.0
This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2018-060,
  author = {Muhammad Imdad Ullah and Muhammad Aslam and Saima Altaf},
  title = {{lmridge: A Comprehensive R Package for the Ridge Regression}},
  year = {2018},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2018-060},
  url = {https://journal.r-project.org/archive/2018/RJ-2018-060/index.html}
}