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
DESCRIPTION
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 3 scripts 393 downloads 13 exports 8 dependencies

Last updated from:c88492cfca. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK185
linux-devel-x86_64OK139
source / vignettesOK236
linux-release-arm64OK144
linux-release-x86_64OK146
macos-release-arm64OK89
macos-release-x86_64OK176
macos-oldrel-arm64OK180
macos-oldrel-x86_64OK354
windows-develOK107
windows-releaseOK123
windows-oldrelOK129
wasm-releaseOK138

Exports:fk_densityfk_ICAfk_mdhfk_pprfk_regressionfk_sumh_Gauss_to_Kh_K_to_Gaussnorm_const_Knorm_Kplot_kernelroughness_Kvar_K

Dependencies:latticeMASSMatrixrARPACKRcppRcppArmadilloRcppEigenRSpectra