A new package crs is introduced for computing nonparametric regression (and quantile) splines in the presence of both continuous and categorical predictors. B-splines are employed in the regression model for the continuous predictors and kernel weighting is employed for the categorical predictors. We also develop a simple R interface to NOMAD, which is a mixed integer optimization solver used to compute optimal regression spline solutions.
crs, SemiPar, mgcv, gss, gam, MASS, rgl
SocialSciences, Econometrics, Environmetrics, Multivariate, Bayesian, Distributions, Graphics, NumericalMathematics, Optimization, Pharmacokinetics, Psychometrics, Robust, SpatioTemporal, Survival
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For attribution, please cite this work as
Nie & Racine, "The R Journal: The crs Package: Nonparametric Regression Splines for Continuous and Categorical Predictors", The R Journal, 2012
BibTeX citation
@article{RJ-2012-012,
author = {Nie, Zhenghua and Racine, Jeffrey S.},
title = {The R Journal: The crs Package: Nonparametric Regression Splines for Continuous and Categorical Predictors},
journal = {The R Journal},
year = {2012},
note = {https://doi.org/10.32614/RJ-2012-012},
doi = {10.32614/RJ-2012-012},
volume = {4},
issue = {2},
issn = {2073-4859},
pages = {48-56}
}