coef.nc.hdsvm: Extract Model Coefficients from a `nc.hdsvm` Object

Description

Retrieves the coefficients at specified values of `lambda` from a fitted `nc.hdsvm()` model.

Usage

# S3 method for nc.hdsvm
coef(object, s = NULL, type = c("coefficients", "nonzero"), ...)

Value

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

Arguments

object: Fitted `nc.hdsvm()` object.
s: Values of the penalty parameter `lambda` for which coefficients are requested. Defaults to the entire sequence used during the model fit.
type: Type of prediction required. Type `"coefficients"` computes the coefficients at the requested values for `s`. Type `"nonzero"` returns a list of the indices of the nonzero coefficients for each value of s.
...: Not used.

Details

This function extracts coefficients for specified `lambda` values from a `nc.hdsvm()` object. If `s`, the vector of `lambda` values, contains values not originally used in the model fitting, the `coef` function employs linear interpolation between the closest `lambda` values from the original sequence to estimate coefficients at the new `lambda` values.

Examples

Run this code

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)) 
nc.fit <- nc.hdsvm(x = x, y = y, lambda = lambda, lam2 = lam2, pen = "scad")
nc.coefs <- coef(nc.fit, s = nc.fit$lambda[3:5])