pense (version 1.2.9)

predict.elnetfit: Predict Method for the classical Elastic Net Estimator

Description

Predict Method for the classical Elastic Net Estimator

Usage

# S3 method for elnetfit
predict(object, newdata, lambda, exact = FALSE, correction = TRUE, ...)

Arguments

object

an object of type elnetfit to use for prediction.

newdata

an optional design matrix

lambda

the value of the penalty parameter. Default is to use the optimal lambda lambda_opt.

exact

if the lambda is not part of the lambda grid, should the estimates be obtained by linear interpolation between the nearest lambda values (default) or computed exactly.

correction

should a correction factor be applied to the EN estimate?

...

currently ignored.

Value

a numeric vector of predicted values for the given lambda.

Examples

# NOT RUN {
# Generate data with highly correlated groups of variables
set.seed(12345)
n <- 100
p <- 20
x <- 1 + matrix(rnorm(n * p), ncol = p)
x[, 2] <- x[, 1] + rnorm(n, sd = 0.01)
x[, 3] <- x[, 1] + rnorm(n, sd = 0.01)
x[, 5] <- x[, 4] + rnorm(n, sd = 0.01)
x[, 6] <- x[, 4] + rnorm(n, sd = 0.01)

y <- drop(x %*% c(rep(c(2, 5), each = 3), numeric(p - 6)) + rnorm(n))

# Compute the classical EN and select the optimal lambda by CV
set.seed(1234)
est_en_cv <- elnet_cv(
    x, y,
    alpha = 0.5,
    correction = TRUE
)

# For cross-validated EN fits, the `coef`, `predict`, and `residuals` methods
# return/use the estimated coefficients at the "optimal" lambda
coef(est_en_cv) # Extract coefficients
predict(est_en_cv) # Extract fitted values
predict(est_en_cv, newdata = x) # Predict values
residuals(est_en_cv) # Extract residuals

# We can also request the coefficient at another lambda. By default,
# this will interpolate between the solutions at the two surrounding
# lambda values.
coef(est_en_cv, lambda = 6)

# If needed, the solution at the given lambda can also be computed exactly.
coef(est_en_cv, lambda = 6, exact = TRUE)


# If we compute the EN estimator without choosing an optimal lambda,
# the lambda parameter needs to be specified in the call to coef
est_en <- elnet(
    x, y,
    alpha = 0.5
)

# Without specifying lambda, the `coef` method would raise an error.
coef(est_en, lambda = 6)
# }