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) <doi:10.48550/arXiv.1303.4121>, Geenens and Wang (2018) <doi:10.48550/arXiv.1602.04862>, Nagler (2018a) <doi:10.48550/arXiv.1704.07457>, Nagler (2018b) <doi:10.48550/arXiv.1705.05431>.

Version: 1.0.7
Imports: graphics, Rcpp, randtoolbox, stats, utils
LinkingTo: BH, Rcpp, RcppEigen
Suggests: testthat
Published: 2024-01-26
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
Materials: README NEWS
CRAN checks: kde1d results


Reference manual: kde1d.pdf


Package source: kde1d_1.0.7.tar.gz
Windows binaries: r-devel: kde1d_1.0.7.zip, r-release: kde1d_1.0.7.zip, r-oldrel: kde1d_1.0.7.zip
macOS binaries: r-release (arm64): kde1d_1.0.7.tgz, r-oldrel (arm64): kde1d_1.0.7.tgz, r-release (x86_64): kde1d_1.0.7.tgz, r-oldrel (x86_64): kde1d_1.0.7.tgz
Old sources: kde1d archive

Reverse dependencies:

Reverse imports: MLCOPULA, rvinecopulib, vinereg
Reverse linking to: portvine, rvinecopulib, vinereg
Reverse suggests: gfilmm


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