SpatialKWD: Spatial KWD for Large Spatial Maps

Contains efficient implementations of Discrete Optimal Transport algorithms for the computation of Kantorovich-Wasserstein distances between pairs of large spatial maps (Bassetti, Gualandi, Veneroni (2020), <doi:10.1137/19M1261195>). All the algorithms are based on an ad-hoc implementation of the Network Simplex algorithm. The package has four main helper functions: compareOneToOne() (to compare two spatial maps), compareOneToMany() (to compare a reference map with a list of other maps), compareAll() (to compute a matrix of distances between a list of maps), and focusArea() (to compute the KWD distance within a focus area). In non-convex maps, the helper functions first build the convex-hull of the input bins and pad the weights with zeros.

Version: 0.4.0
Imports: methods, Rcpp
LinkingTo: Rcpp
Published: 2021-05-07
Author: Stefano Gualandi [aut, cre]
Maintainer: Stefano Gualandi <stefano.gualandi at gmail.com>
License:
NeedsCompilation: yes
SystemRequirements: C++11
CRAN checks: SpatialKWD results

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Reference manual: SpatialKWD.pdf
Package source: SpatialKWD_0.4.0.tar.gz
Windows binaries: r-devel: SpatialKWD_0.4.0.zip, r-release: not available, r-oldrel: SpatialKWD_0.4.0.zip
macOS binaries: r-release: SpatialKWD_0.4.0.tgz, r-oldrel: SpatialKWD_0.4.0.tgz
Old sources: SpatialKWD archive

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