kde1d: Univariate Kernel Density Estimation

Provides an efficient implementation of univariate local polynomial kernel density estimators that can handle bounded and discrete data. See Geenens (2014) <arXiv:1303.4121>, Geenens and Wang (2018) <arXiv:1602.04862>, Nagler (2018a) <arXiv:1704.07457>, Nagler (2018b) <arXiv:1705.05431>.

Version: 0.1.2
Imports: cctools, graphics, Rcpp, qrng, stats, utils
LinkingTo: BH, Rcpp, RcppEigen
Suggests: testthat
Published: 2018-04-17
Author: Thomas Nagler [aut, cre], Thibault Vatter [aut]
Maintainer: Thomas Nagler <mail at tnagler.com>
BugReports: https://github.com/tnagler/kde1d/issues
License: MIT + file LICENSE
URL: https://github.com/tnagler/kde1d
NeedsCompilation: yes
SystemRequirements: C++11
Materials: README NEWS
CRAN checks: kde1d results


Reference manual: kde1d.pdf
Package source: kde1d_0.1.2.tar.gz
Windows binaries: r-prerel: kde1d_0.1.2.zip, r-release: kde1d_0.1.2.zip, r-oldrel: kde1d_0.1.2.zip
OS X binaries: r-prerel: kde1d_0.1.2.tgz, r-release: kde1d_0.1.2.tgz
Old sources: kde1d archive


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