pgKDEsphere: Parametrically Guided Kernel Density Estimator for Spherical Data

Nonparametric density estimation for (hyper)spherical data by means of a parametrically guided kernel estimator (adaptation of the method of Hjort and Glad (1995) <doi:10.1214/aos/1176324627> to the spherical setting). 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: 1.0.1
Imports: Rcpp (≥ 1.0.11), rgl, Directional, DirStats, circular, matrixStats, rotasym, movMF
LinkingTo: Rcpp, RcppArmadillo
Published: 2024-02-07
Author: María Alonso-Pena [aut, cre], Gerda Claeskens [aut], Irène Gijbels [aut]
Maintainer: María Alonso-Pena <maria.alonsopena at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: pgKDEsphere results


Reference manual: pgKDEsphere.pdf


Package source: pgKDEsphere_1.0.1.tar.gz
Windows binaries: r-prerel:, r-release:, r-oldrel:
macOS binaries: r-prerel (arm64): pgKDEsphere_1.0.1.tgz, r-release (arm64): pgKDEsphere_1.0.1.tgz, r-oldrel (arm64): pgKDEsphere_1.0.1.tgz, r-prerel (x86_64): pgKDEsphere_1.0.1.tgz, r-release (x86_64): pgKDEsphere_1.0.1.tgz


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