Package: GWnnegPCA 0.0.5

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_0.0.5.tar.gz
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GWnnegPCA.pdf |GWnnegPCA.html✨
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:

3.00 score 375 downloads 1 exports 15 dependencies

Last updated 2 months agofrom:4abc5da939. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 07 2025
R-4.5-winOKMar 07 2025
R-4.5-macOKMar 07 2025
R-4.5-linuxOKMar 07 2025
R-4.4-winOKMar 07 2025
R-4.4-macOKMar 07 2025
R-4.4-linuxOKMar 07 2025
R-4.3-winOKMar 07 2025
R-4.3-macOKMar 07 2025

Exports:gw_nsprcomp

Dependencies:classclassIntDBIe1071geodistKernSmoothmagrittrMASSnsprcompproxyRcpps2sfunitswk