predict.vinereg: Predict conditional mean and quantiles from a D-vine...

In vinereg: D-Vine Quantile Regression

Predict conditional mean and quantiles from a D-vine regression model

Description

Predict conditional mean and quantiles from a D-vine regression model

Usage

## S3 method for class 'vinereg'
predict(object, newdata, alpha = 0.5, cores = 1, ...)

## S3 method for class 'vinereg'
fitted(object, alpha = 0.5, ...)

Arguments

object	an object of class vinereg.
newdata	matrix of covariate values for which to predict the quantile.
alpha	vector of quantile levels; NA predicts the mean based on an average of the 1:10 / 11-quantiles.
cores	integer; the number of cores to use for computations.
...	unused.

Value

A data.frame of quantiles where each column corresponds to one value of alpha.

See Also

vinereg

Examples

# simulate data
x <- matrix(rnorm(200), 100, 2)
y <- x %*% c(1, -2)
dat <- data.frame(y = y, x = x, z = as.factor(rbinom(100, 2, 0.5)))

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

# inspect model
summary(fit)
plot_effects(fit)

# model predictions
mu_hat <- predict(fit, newdata = dat, alpha = NA) # mean
med_hat <- predict(fit, newdata = dat, alpha = 0.5) # median

# observed vs predicted
plot(cbind(y, mu_hat))

## fixed variable order (no selection)
(fit <- vinereg(y ~ ., dat, order = c("x.2", "x.1", "z.1")))

vinereg documentation built on March 23, 2022, 5:06 p.m.