Plot Optimal Transport inner statistics — plot_inner

Plot Optimal Transport based inner statistics for each partition using ggplot2 package. If provided, it plots also the uncertainty estimates.

Usage

plot_inner_stats(x, ranking = NULL, wb_all = FALSE, ...)

Arguments

x: An object generated by ot_indices, ot_indices_1d, or ot_indices_wb.
ranking: An integer with absolute value less or equal than the number of inputs. If positive, select the first ranking inputs per importance. If negative, select the last ranking inputs per importance.
wb_all: (default FALSE) Logical that defines whether or not to plot the Advective and Diffusive components of the Wasserstein-Bures indices
...: Further arguments passed to or from other methods.

Value

A patchwork object that, if called, will print.

Examples

N <- 1000

mx <- c(1, 1, 1)
Sigmax <- matrix(data = c(1, 0.5, 0.5, 0.5, 1, 0.5, 0.5, 0.5, 1), nrow = 3)

x1 <- rnorm(N)
x2 <- rnorm(N)
x3 <- rnorm(N)

x <- cbind(x1, x2, x3)
x <- mx + x %*% chol(Sigmax)

A <- matrix(data = c(4, -2, 1, 2, 5, -1), nrow = 2, byrow = TRUE)
y <- t(A %*% t(x))

x <- data.frame(x)

M <- 25

# Get sensitivity indices
sensitivity_indices <- ot_indices(x, y, M)
#> Using default values for solver sinkhorn 
plot_inner_stats(sensitivity_indices)