pgKDEsphere: Parametrically Guided Kernel Density Estimator for Spherical Data

Nonparametric density estimation for (hyper)spherical data by means of a parametrically guided kernel estimator (Alonso-Pena et al. (2024) <doi:10.1111/sjos.12737>. The package also allows the data-driven selection of the smoothing parameter and the representation of the estimated density for circular and spherical data. Estimators of the density without guide can also be obtained.

Version:	1.0.2
Imports:	Rcpp (≥ 1.0.11), rgl, Directional, DirStats, circular, matrixStats, rotasym, movMF
LinkingTo:	Rcpp, RcppArmadillo
Published:	2025-10-28
DOI:	10.32614/CRAN.package.pgKDEsphere
Author:	María Alonso-Pena [aut, cre], Gerda Claeskens [aut], Irène Gijbels [aut]
Maintainer:	María Alonso-Pena <mariaalonso.pena at usc.es>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	yes
CRAN checks:	pgKDEsphere results

Documentation:

Reference manual:

pgKDEsphere.html , pgKDEsphere.pdf

Downloads:

Package source:	pgKDEsphere_1.0.2.tar.gz
Windows binaries:	r-devel: pgKDEsphere_1.0.1.zip, r-release: pgKDEsphere_1.0.2.zip, r-oldrel: pgKDEsphere_1.0.1.zip
macOS binaries:	r-release (arm64): pgKDEsphere_1.0.2.tgz, r-oldrel (arm64): pgKDEsphere_1.0.2.tgz, r-release (x86_64): pgKDEsphere_1.0.2.tgz, r-oldrel (x86_64): pgKDEsphere_1.0.2.tgz
Old sources:	pgKDEsphere archive

Linking:

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