predict.nc.hdqr: Make Predictions from a 'nc.hdqr' Object

In hdqr: Fast Algorithm for Penalized Quantile Regression

Make Predictions from a 'nc.hdqr' Object

Description

Produces fitted values for new predictor data using a fitted 'nc.hdqr()' object.

Usage

## S3 method for class 'nc.hdqr'
predict(object, newx, s = NULL, ...)

Arguments

object	Fitted 'nc.hdqr()' object from which predictions are to be derived.
newx	Matrix of new predictor values for which predictions are desired. This must be a matrix and is a required argument.
s	Values of the penalty parameter 'lambda' for which predictions are requested. Defaults to the entire sequence used during the model fit.
...	Not used.

Details

This function generates predictions at specified 'lambda' values from a fitted 'nc.hdqr()' object. It is essential to provide a new matrix of predictor values ('newx') at which these predictions are to be made.

Value

Returns a vector or matrix of predicted values corresponding to the specified 'lambda' values.

See Also

nc.hdqr, coef.nc.hdqr

Examples

set.seed(315)
n <- 100
p <- 400
x <- matrix(data = rnorm(n * p, mean = 0, sd = 1), nrow = n, ncol = p)
beta_star <- c(c(2, 1.5, 0.8, 1, 1.75, 0.75, 0.3), rep(0, (p - 7)))
eps <- rnorm(n, mean = 0, sd = 1)
y <- x %*% beta_star + eps
tau <- 0.5
lam2 <- 0.01
lambda <- 10^(seq(1,-4, length.out=30))
nc.fit <- nc.hdqr(x=x, y=y, tau=tau, lambda=lambda, lam2=lam2, pen="scad")
nc.preds <- predict(nc.fit, newx = tail(x), s = nc.fit$lambda[3:5])

hdqr documentation built on April 3, 2025, 6:20 p.m.