Package: FKSUM 1.0.1

David P. Hofmeyr

FKSUM: Fast Kernel Sums

Implements the method of Hofmeyr, D.P. (2021) <doi:10.1109/TPAMI.2019.2930501> for fast evaluation of univariate kernel smoothers based on recursive computations. Applications to the basic problems of density and regression function estimation are provided, as well as some projection pursuit methods for which the objective is based on non-parametric functionals of the projected density, or conditional density of a response given projected covariates. The package is accompanied by an instructive paper in the Journal of Statistical Software <doi:10.18637/jss.v101.i03>.

Authors:David P. Hofmeyr

FKSUM_1.0.1.tar.gz
FKSUM_1.0.1.zip(r-4.7)FKSUM_1.0.1.zip(r-4.6)FKSUM_1.0.1.zip(r-4.5)
FKSUM_1.0.1.tgz(r-4.6-x86_64)FKSUM_1.0.1.tgz(r-4.6-arm64)FKSUM_1.0.1.tgz(r-4.5-x86_64)FKSUM_1.0.1.tgz(r-4.5-arm64)
FKSUM_1.0.1.tar.gz(r-4.7-arm64)FKSUM_1.0.1.tar.gz(r-4.7-x86_64)FKSUM_1.0.1.tar.gz(r-4.6-arm64)FKSUM_1.0.1.tar.gz(r-4.6-x86_64)
FKSUM_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
FKSUM/json (API)

# Install 'FKSUM' in R:
install.packages('FKSUM', repos = c('https://davidhofmeyr.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

1.48 score 1 packages 2 scripts 220 downloads 13 exports 8 dependencies

Last updated from:c88492cfca. Checks:12 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK141
source / vignettesOK176
linux-release-arm64OK136
linux-release-x86_64OK150
macos-release-arm64OK155
macos-release-x86_64OK286
macos-oldrel-arm64OK96
macos-oldrel-x86_64OK356
windows-develOK147
windows-releaseOK126
windows-oldrelOK204
wasm-releaseOK96

Exports:fk_densityfk_ICAfk_mdhfk_pprfk_regressionfk_sumh_Gauss_to_Kh_K_to_Gaussnorm_const_Knorm_Kplot_kernelroughness_Kvar_K

Dependencies:latticeMASSMatrixrARPACKRcppRcppArmadilloRcppEigenRSpectra