ridgePlot: Ridge Plots for a Range of Coefficients

In WpProj: Linear p-Wasserstein Projections

Ridge Plots for a Range of Coefficients

Description

This function will plot the distribution of predictions for a range of active coefficients

Usage

ridgePlot(
  fit,
  index = 1,
  minCoef = 1,
  maxCoef = 10,
  scale = 1,
  alpha = 0.5,
  full = NULL,
  transform = function(x) {
     x
 },
  xlab = "Predictions",
  bandwidth = NULL
)

Arguments

fit	A WpProj object or list of WpProj objects
index	The observation number to select. Can be a vector
minCoef	The minimum number of coefficients to use
maxCoef	The maximum number of coefficients to use
scale	How the densities should be scale
alpha	Alpha term from ggplot2 object
full	"True" prediction to compare to
transform	transform for predictions
xlab	x-axis label
bandwidth	Bandwidth for kernel

Value

a ggplot2::ggplot() plot

Examples

if(rlang::is_installed("stats")) {
n <- 128
p <- 10
s <- 99
x <- matrix(stats::rnorm(n*p), nrow = n, ncol = p )
beta <- (1:10)/10
y <- x %*% beta + stats::rnorm(n)
post_beta <- matrix(beta, nrow=p, ncol=s) + matrix(stats::rnorm(p*s, 0, 0.1), p, s)
post_mu <- x %*% post_beta
fit <-  WpProj(X=x, eta=post_mu, 
             power = 2
)
ridgePlot(fit)
}

WpProj documentation built on May 29, 2024, 7:55 a.m.