np: Nonparametric kernel smoothing methods for mixed data types

This package provides a variety of nonparametric (and semiparametric) kernel methods that seamlessly handle a mix of continuous, unordered, and ordered factor data types. We would like to gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada (NSERC:www.nserc.ca), the Social Sciences and Humanities Research Council of Canada (SSHRC:www.sshrc.ca), and the Shared Hierarchical Academic Research Computing Network (SHARCNET:www.sharcnet.ca).

Version: 0.60-2
Imports: boot, cubature, stats
Suggests: quantreg, MASS
Published: 2014-06-28
Author: Jeffrey S. Racine [aut, cre], Tristen Hayfield [aut]
Maintainer: Jeffrey S. Racine <racinej at mcmaster.ca>
License: GPL-2 | GPL-3 [expanded from: GPL]
Copyright: see file COPYRIGHTS
URL: https://github.com/JeffreyRacine/R-Package-np/
NeedsCompilation: yes
Citation: np citation info
Materials: README ChangeLog
In views: Econometrics, SocialSciences
CRAN checks: np results

Downloads:

Reference manual: np.pdf
Vignettes: Entropy-based Inference Using the np Package
The np Package
Frequently Asked Questions (np)
Package source: np_0.60-2.tar.gz
Windows binaries: r-devel: np_0.60-2.zip, r-release: np_0.60-2.zip, r-oldrel: np_0.60-2.zip
OS X Snow Leopard binaries: r-release: np_0.60-2.tgz, r-oldrel: np_0.60-2.tgz
OS X Mavericks binaries: r-release: np_0.60-2.tgz
Old sources: np archive

Reverse dependencies:

Reverse depends: CovSel, DepthProc, rddtools, semsfa, stam
Reverse imports: crs, npbr, NSM3, treeclim
Reverse suggests: AER