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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

1,694

Version

0.15-38

License

GPL (>= 3)

Issues

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Stars

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Maintainer

Last Published

September 29th, 2024

Functions in crs (0.15-38)

clsd

Categorical Logspline Density
Engel95

1995 British Family Expenditure Survey
wage1

Cross-Sectional Data on Wages
cps71

Canadian High School Graduate Earnings
frscv

Categorical Factor Regression Spline Cross-Validation
crs-package

Nonparametric Regression Splines with Continuous and Categorical Predictors
crssigtest

Regression Spline Significance Test with Mixed Data Types
crsivderiv

Nonparametric Instrumental Derivatives
crsiv

Nonparametric Instrumental Regression
krscvNOMAD

Categorical Kernel Regression Spline Cross-Validation
crs

Categorical Regression Splines
gsl.bs

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

Categorical Factor Regression Spline Cross-Validation
krscv

Categorical Kernel Regression Spline Cross-Validation
tensor.prod.model.matrix

Utility functions for constructing tensor product smooths
glp.model.matrix

Utility function for constructing generalized polynomial smooths
npglpreg

Generalized Local Polynomial Regression
uniquecombs

Find the unique rows in a matrix
snomadr

R interface to NOMAD