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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

1,231

Version

0.15-33

License

GPL (>= 3)

Issues

Pull Requests

Stars

Forks

Maintainer

Jeffrey Racine

Last Published

February 2nd, 2021

Functions in crs (0.15-33)

krscvNOMAD

Categorical Kernel Regression Spline Cross-Validation
npglpreg

Generalized Local Polynomial Regression
crsiv

Nonparametric Instrumental Regression
crs

Categorical Regression Splines
crsivderiv

Nonparametric Instrumental Derivatives
Engel95

1995 British Family Expenditure Survey
crssigtest

Regression Spline Significance Test with Mixed Data Types
snomadr

R interface to NOMAD
frscvNOMAD

Categorical Factor Regression Spline Cross-Validation
cps71

Canadian High School Graduate Earnings
glp.model.matrix

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

Utility functions for constructing tensor product smooths
wage1

Cross-Sectional Data on Wages
frscv

Categorical Factor Regression Spline Cross-Validation
gsl.bs

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

Categorical Kernel Regression Spline Cross-Validation
crs-package

Nonparametric Regression Splines with Continuous and Categorical Predictors
clsd

Categorical Logspline Density
uniquecombs

Find the unique rows in a matrix