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 (Tsutsumida N. et al., (2019) <doi:10.17608/k6.auckland.9850826.v1>).

Version: 0.0.1
Depends: R (≥ 3.5.0)
Imports: sp, sf, GWmodel, nsprcomp, methods
Published: 2020-03-24
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

Downloads:

Reference manual: GWnnegPCA.pdf
Package source: GWnnegPCA_0.0.1.tar.gz
Windows binaries: r-devel: GWnnegPCA_0.0.1.zip, r-release: GWnnegPCA_0.0.1.zip, r-oldrel: GWnnegPCA_0.0.1.zip
macOS binaries: r-release: GWnnegPCA_0.0.1.tgz, r-oldrel: GWnnegPCA_0.0.1.tgz

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