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]

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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'))

Peer review:

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

On CRAN:

2.70 score 173 downloads 1 exports 19 dependencies

Last updated 4 years agofrom:7453e6a597. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 27 2024
R-4.5-winNOTEOct 27 2024
R-4.5-linuxNOTEOct 27 2024
R-4.4-winNOTEOct 27 2024
R-4.4-macNOTEOct 27 2024
R-4.3-winNOTEOct 27 2024
R-4.3-macNOTEOct 27 2024

Exports:gw_nsprcomp

Dependencies:classclassIntDBIe1071geodistKernSmoothlatticemagrittrMASSnsprcomppracmaproxyRcpps2sfspspDataunitswk