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>.

Version: 0.0.4
Depends: R (≥ 3.5.0)
Imports: sp, sf, pracma, geodist, nsprcomp, methods, spData
Published: 2020-11-18
DOI: 10.32614/CRAN.package.GWnnegPCA
Author: Narumasa Tsutsumida ORCID iD [aut, cre]
Maintainer: Narumasa Tsutsumida <rsnaru.jp at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
SystemRequirements: C++11, GDAL (>= 2.0.1), GEOS (>= 3.4.0), PROJ (>= 4.8.0)
Language: en-US
Materials: README
CRAN checks: GWnnegPCA results

Documentation:

Reference manual: GWnnegPCA.pdf

Downloads:

Package source: GWnnegPCA_0.0.4.tar.gz
Windows binaries: r-devel: GWnnegPCA_0.0.4.zip, r-release: GWnnegPCA_0.0.4.zip, r-oldrel: GWnnegPCA_0.0.4.zip
macOS binaries: r-release (arm64): GWnnegPCA_0.0.4.tgz, r-oldrel (arm64): GWnnegPCA_0.0.4.tgz, r-release (x86_64): GWnnegPCA_0.0.4.tgz, r-oldrel (x86_64): GWnnegPCA_0.0.4.tgz
Old sources: GWnnegPCA archive

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