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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 [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 |
Reference manual: | GWnnegPCA.pdf |
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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.