np: Nonparametric Kernel Smoothing Methods for Mixed Data Types

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, <>), the Social Sciences and Humanities Research Council of Canada (SSHRC, <>), and the Shared Hierarchical Academic Research Computing Network (SHARCNET, <>).

Version: 0.60-9
Imports: boot, cubature, methods, quadprog, quantreg, stats
Suggests: MASS
Published: 2018-10-25
Author: Jeffrey S. Racine [aut, cre], Tristen Hayfield [aut]
Maintainer: Jeffrey S. Racine <racinej at>
License: GPL-2 | GPL-3 [expanded from: GPL]
Copyright: see file COPYRIGHTS
NeedsCompilation: yes
Citation: np citation info
Materials: README ChangeLog
In views: Econometrics, SocialSciences
CRAN checks: np results


Reference manual: np.pdf
Vignettes: Entropy-based Inference Using the np Package
The np Package
Frequently Asked Questions (np)
Package source: np_0.60-9.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: np_0.60-9.tgz, r-oldrel: np_0.60-9.tgz
Old sources: np archive

Reverse dependencies:

Reverse depends: causalweight, CovSel, DepthProc, FIAR, generalCorr, rddtools, semsfa, stam
Reverse imports: analytics, anchoredDistr, AROC, CARS, Compind, condSURV, crs, drtmle, lg, MaskJointDensity, npbr, nse, NSM3, pssmooth, rpatrec, simIReff, survidm, treeclim
Reverse suggests: AER, BNSP, mlt.docreg, spaero


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