Conditional probability integral transform

Evaluates the fitted conditional distribution of the response given the covariates. For a discrete response, this is the conditional CDF at the observed category, not a randomized probability integral transform.

Usage

cpit(object, newdata, cores = 1)

Arguments

object

an object of class vinereg.

newdata

a data frame containing the response and covariates from the original formula, with matching classes and factor levels.

cores

integer; the number of cores to use for computations.

Value

A numeric vector containing one conditional CDF value per row of newdata.

Examples

# simulate data
x <- matrix(rnorm(100), 50, 2)
y <- x %*% c(1, -2)
dat <- data.frame(y = y, x = x, z = as.factor(rbinom(50, 2, 0.5)))

# fit vine regression model
fit <- vinereg(y ~ ., dat)

hist(cpit(fit, dat)) # should be approximately uniform