hdsvm (version 1.0.2)

coef.cv.hdsvm: Extract Coefficients from a `cv.hdsvm` Object

Description

Retrieves coefficients from a cross-validated `hdsvm()` model, using the stored `"hdsvm.fit"` object and the optimal `lambda` value determined during cross-validation.

Usage

# S3 method for cv.hdsvm
coef(object, s = c("lambda.1se", "lambda.min"), ...)

Value

Returns the coefficients at the specified `lambda` values.

Arguments

object

A fitted `cv.hdsvm()` object from which coefficients are to be extracted.

s

Specifies the value(s) of the penalty parameter `lambda` for which coefficients are desired. The default is `s = "lambda.1se"`, which corresponds to the largest value of `lambda` such that the cross-validation error estimate is within one standard error of the minimum. Alternatively, `s = "lambda.min"` can be used, corresponding to the minimum of the cross-validation error estimate. If `s` is numeric, these are taken as the actual values of `lambda` to use.

...

Not used.

See Also

cv.hdsvm, predict.cv.hdsvm

Examples

set.seed(315)
n <- 100
p <- 400
x1 <- matrix(rnorm(n / 2 * p, -0.25, 0.1), n / 2)
x2 <- matrix(rnorm(n / 2 * p, 0.25, 0.1), n / 2)
x <- rbind(x1, x2)
beta <- 0.1 * rnorm(p)
prob <- plogis(c(x %*% beta))
y <- 2 * rbinom(n, 1, prob) - 1
cv.fit <- cv.hdsvm(x, y, lam2 = 0.01)
coef(cv.fit, s = c(0.02, 0.03))