testOTM is an R package that computes multivariate ranks and quantiles defined through the theory of optimal transportation. It also provides several applications of these statistics, most notably a method for two-sample multivariate goodness-of-fit testing.
You can install the released version of
testOTM from CRAN with:
You can install the development version from GitHub with:
# install.packages("devtools") # devtools::install_github("Francis-Hsu/testOTM")
This is a basic example which shows you how to use
testOTM to visualize the optimal transport map from $U[0, 1]^2$ to a (scaled) bivariate normal sample:
library(testOTM) # generate bivariate normal data p = 2 n = 100 Sigma = matrix(c(2, 1, 1, 2), 2, 2) eS = eigen(Sigma, symmetric = TRUE) X = t(eS$vectors %*% diag(sqrt(pmax(eS$values, 0)), p) %*% matrix(rnorm(p * n), p)) # compute the optimal transport map from U[0, 1]^2 to the data # notice that the data will be scale into [0, 1] range X.OTM = tos.fit(X) # plot the restricted Voronoi diagram and the restricted Delaunay triangulation par(mfrow = c(1, 2)) plot(X.OTM, which = "Both", draw.center = F, draw.map = T)
The author is extremely grateful to Prof. Bodhisattva Sen and his student Promit Ghosal for their guidance in the development of this package. The author would also like to thank Dr. Bruno Lévy for his assistance with the Geogram library, and the TraME team, whose
Rgeogram package provides inspirations to the early build of this package.
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