kde1d: Univariate Kernel Density Estimation
Provides an efficient implementation of univariate local polynomial
kernel density estimators that can handle bounded, discrete, and zero-inflated
data. See Geenens and Wang (2018) <doi:10.48550/arXiv.1602.04862>,
Geenens (2014) <doi:10.48550/arXiv.1303.4121>,
Nagler (2018a) <doi:10.48550/arXiv.1704.07457>,
Nagler (2018b) <doi:10.48550/arXiv.1705.05431>.
| Version: |
1.2.0 |
| Imports: |
graphics, Rcpp, randtoolbox, stats, utils |
| LinkingTo: |
BH, Rcpp, RcppEigen |
| Suggests: |
BH, RcppEigen, testthat |
| Published: |
2026-09-10 |
| DOI: |
10.32614/CRAN.package.kde1d |
| 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://tnagler.github.io/kde1d/ |
| NeedsCompilation: |
yes |
| Materials: |
README, NEWS |
| CRAN checks: |
kde1d results |
Documentation:
Downloads:
Reverse dependencies:
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