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SpatialKWD
View on CRAN: Click
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Download and install SpatialKWD package within the R console
Install from CRAN:
install.packages("SpatialKWD")
Install from Github:
library("remotes")
install_github("cran/SpatialKWD") Install by package version:
library("remotes")
install_version("SpatialKWD", "0.4.1") Attach the package and use:
library("SpatialKWD")
Maintained by
Stefano Gualandi
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First Published: 2021-03-31
Latest Update: 2022-12-09
Description:
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.
How to cite:
Stefano Gualandi (2021). SpatialKWD: Spatial KWD for Large Spatial Maps. R package version 0.4.1, https://cran.r-project.org/web/packages/SpatialKWD. Accessed 18 Sep. 2026.
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Complete documentation for SpatialKWD
Functions, R codes and Examples using
the SpatialKWD R package
Some associated functions: SpatialKWD-package .
Some associated R codes: RcppExports.R . zzz.R . Full SpatialKWD package functions and examples
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