The Liu regression estimator is now a commonly used alternative to the conventional ordinary least squares estimator that avoids the adverse effects in the situations when there exists a considerable degree of multicollinearity among the regressors. There are only a few software packages available for estimation of the Liu regression coefficients, though with limited methods to estimate the Liu biasing parameter without addressing testing procedures. Our liureg package can be used to estimate the Liu regression coefficients utilizing a range of different existing biasing parameters, to test these coefficients with more than 15 Liu related statistics, and to present different graphical displays of these statistics.
Supplementary materials are available in addition to this article. It can be downloaded at RJ-2017-048.zip
lrmest, ltsbase, liureg, lmridge, MASS, mctest
Distributions, Econometrics, Environmetrics, Multivariate, NumericalMathematics, Psychometrics, Robust, SocialSciences
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For attribution, please cite this work as
Imdadullah, et al., "The R Journal: liureg: A Comprehensive R Package for the Liu Estimation of Linear Regression Model with Collinear Regressors", The R Journal, 2017
BibTeX citation
@article{RJ-2017-048,
author = {Imdadullah, Muhammad and Aslam, Muhammad and Altaf, Saima},
title = {The R Journal: liureg: A Comprehensive R Package for the Liu Estimation of Linear Regression Model with Collinear Regressors},
journal = {The R Journal},
year = {2017},
note = {https://doi.org/10.32614/RJ-2017-048},
doi = {10.32614/RJ-2017-048},
volume = {9},
issue = {2},
issn = {2073-4859},
pages = {232-247}
}