Package: GWnnegPCA 0.0.6

GWnnegPCA: Geographically Weighted Non-Negative Principal Components Analysis

Implements a geographically weighted non-negative principal components analysis, which consists of the fusion of geographically weighted and sparse non-negative principal components analyses <doi:10.17608/k6.auckland.9850826.v1>.

Authors:Narumasa Tsutsumida [aut, cre]

GWnnegPCA_0.0.6.tar.gz
GWnnegPCA_0.0.6.zip(r-4.7)GWnnegPCA_0.0.6.zip(r-4.6)GWnnegPCA_0.0.6.zip(r-4.5)
GWnnegPCA_0.0.6.tgz(r-4.6-any)GWnnegPCA_0.0.6.tgz(r-4.5-any)
GWnnegPCA_0.0.6.tar.gz(r-4.7-any)GWnnegPCA_0.0.6.tar.gz(r-4.6-any)
GWnnegPCA_0.0.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
GWnnegPCA/json (API)

# Install 'GWnnegPCA' in R:
install.packages('GWnnegPCA', repos = c('https://naru-t.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/naru-t/gwnnegpca/issues

On CRAN:

Conda:

2.70 score 1 stars 2 scripts 202 downloads 1 exports 14 dependencies

Last updated from:e13eb3de89. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK126
source / vignettesOK178
linux-release-x86_64OK130
macos-release-arm64OK203
macos-oldrel-arm64OK186
windows-develOK86
windows-releaseOK85
windows-oldrelOK73
wasm-releaseOK106

Exports:gw_nsprcomp

Dependencies:classclassIntDBIe1071geodistKernSmoothMASSnsprcompproxyRcpps2sfunitswk