coef.cv.nc.hdsvm: Extract Coefficients from a 'cv.nc.hdsvm' Object

In hdsvm: Fast Algorithm for Support Vector Machine

Extract Coefficients from a 'cv.nc.hdsvm' Object

Description

Retrieves coefficients at specified values of 'lambda' from a fitted 'cv.nc.hdsvm()' model. Utilizes the stored '"nchdsvm.fit"' object and the optimal 'lambda' values determined during the cross-validation process.

Usage

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

Arguments

object	A fitted 'cv.nc.hdsvm()' object from which coefficients are to be extracted.
s	Specifies the 'lambda' values at which coefficients are requested. The default is 's = "lambda.1se"', representing the largest 'lambda' such that the cross-validation error estimate is within one standard error of the minimum. Alternatively, 's = "lambda.min"' corresponds to the 'lambda' yielding the minimum cross-validation error. If 's' is numeric, these values are directly used as the 'lambda' values for coefficient extraction.
...	Not used.

Value

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

See Also

cv.nc.hdsvm, predict.cv.nc.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
lam2 <- 0.01
lambda <- 10^(seq(1,-4, length.out = 30))
cv.nc.fit <- cv.nc.hdsvm(x = x, y = y, lambda = lambda, lam2 = lam2, pen = "scad")
coef(cv.nc.fit, s = c(0.02, 0.03))

hdsvm documentation built on April 12, 2025, 1:27 a.m.