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crs

This is the R package `crs' (Categorical Regression Splines) written and maintained by Jeffrey S. Racine (racinej@mcmaster.ca) with the invaluable assistance of Zhenghua Nie.

Installation

You can install the stable version on CRAN:

install.packages('crs', dependencies = TRUE)

Or download the zip ball or tar ball, decompress and run R CMD INSTALL on it, or install then use the devtools package to install the development version:

library(devtools); install_github('R-Package-crs', 'JeffreyRacine')

Note Windows users have to first install Rtools, while OS X users have to first install Xcode and the command line tools (in OS X 10.9 or higher, once you have Xcode installed, open a terminal and run xcode-select --install).

For more information on this project please visit the maintainer's website (https://www.socialsciences.mcmaster.ca/people/racinej).

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Version

Install

install.packages('crs')

Monthly Downloads

3,760

Version

0.15-39

License

GPL (>= 3)

Issues

Pull Requests

Stars

Forks

Maintainer

Jeffrey Racine

Last Published

January 29th, 2026

Functions in crs (0.15-39)

crs

Categorical Regression Splines
crs-package

Nonparametric Regression Splines with Continuous and Categorical Predictors
crssigtest

Regression Spline Significance Test with Mixed Data Types
cps71

Canadian High School Graduate Earnings
frscv

Categorical Factor Regression Spline Cross-Validation
clsd

Categorical Logspline Density
crsivderiv

Nonparametric Instrumental Derivatives
crsiv

Nonparametric Instrumental Regression
Engel95

1995 British Family Expenditure Survey
wage1

Cross-Sectional Data on Wages
krscvNOMAD

Categorical Kernel Regression Spline Cross-Validation
npglpreg

Generalized Local Polynomial Regression
gsl.bs

GSL (GNU Scientific Library) B-spline/B-spline Derivatives
krscv

Categorical Kernel Regression Spline Cross-Validation
uniquecombs

Find the unique rows in a matrix
frscvNOMAD

Categorical Factor Regression Spline Cross-Validation
snomadr

R interface to NOMAD
glp.model.matrix

Utility function for constructing generalized polynomial smooths
tensor.prod.model.matrix

Utility functions for constructing tensor product smooths