hdqr (version 1.0.2)

predict.nc.hdqr: 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 nc.hdqr
predict(object, newx, s = NULL, ...)

Value

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

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.

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])