WPR2: W_p R^2 Function to Evaluate Performance

In WpProj: Linear p-Wasserstein Projections

W_p R^2 Function to Evaluate Performance

Description

This function will calculate p-Wasserstein distances between the predictions of interest and the projected model.

Usage

WPR2(
  predictions = NULL,
  projected_model,
  p = 2,
  method = "exact",
  base = NULL,
  ...
)

## S4 method for signature 'ANY,matrix'
WPR2(
  predictions = NULL,
  projected_model,
  p = 2,
  method = "exact",
  base = NULL,
  ...
)

## S4 method for signature 'ANY,distcompare'
WPR2(
  predictions = NULL,
  projected_model,
  p = 2,
  method = "exact",
  base = NULL,
  ...
)

## S4 method for signature 'ANY,list'
WPR2(
  predictions = NULL,
  projected_model,
  p = 2,
  method = "exact",
  base = NULL,
  ...
)

## S4 method for signature 'ANY,WpProj'
WPR2(
  predictions = NULL,
  projected_model,
  p = 2,
  method = "exact",
  base = NULL,
  ...
)

Arguments

predictions	Predictions of interest, likely from the original model
projected_model	A matrix of competing predictions, possibly from a WpProj fit, a WpProj fit itself, or a list of WpProj objects
p	Power of the Wasserstein distance to use in distance calculations
method	Method for calculating Wasserstein distance
base	The baseline result to compare to. If not provided, defaults to the model with no covariates and only an intercept.
...	Arguments passed to Wasserstein distance calculation. See wasserstein

Value

W_p R ^2 values

Examples

if (rlang::is_installed("stats")) {
# this example is not a true posterior estimation, but is used for illustration
n <- 32
p <- 10
s <- 21
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(rnorm(p*s), p, s) # not a true posterior
post_mu <- x %*% post_beta

fit <-  WpProj(X=x, eta=post_mu, power = 2.0)

out <- WPR2(predictions = post_mu, projected_model = fit, 
base = rowMeans(post_mu) # same as intercept only projection
)
}

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