predict.vinereg {vinereg} | R Documentation |
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 |
newdata |
matrix of covariate values for which to predict the quantile. |
alpha |
vector of quantile levels; |
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
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")))
[Package vinereg version 0.10.0 Index]