# predict.vinereg: Predict conditional mean and quantiles from a D-vine... In vinereg: D-Vine Quantile Regression

 predict.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 `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`.

`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 Nov. 2, 2023, 5:51 p.m.