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SpatialKWD  

Spatial KWD for Large Spatial Maps
View on CRAN: Click here


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
[Scholar Profile | Author Map]
All associated links for this package
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 10 Oct. 2026.
Previous versions and publish date:
(2026-07-09 08:26), 0.3.0 (2021-03-31 10:30), 0.3.1 (2021-04-16 09:30), 0.4.0 (2021-05-07 14:50), 0.4.1 (2022-12-09 18:00)
Other packages that cited SpatialKWD R package
View SpatialKWD citation profile
Other R packages that SpatialKWD depends, imports, suggests or enhances
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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