coef.sgp.cv: Coefficients from SGP models

In SGPR: Sparse Group Penalized Regression for Bi-Level Variable Selection

Coefficients from SGP models

Description

A function that extracts the estimated coefficients from an cross-validated SGP object.

Usage

## S3 method for class 'sgp.cv'
coef(object, lambda = object$lambda.min, index = object$min, ...)

Arguments

object	A object that was generated with sgp.cv.
lambda	The value of lambda at which the coefficients are to be extracted.
index	The index that indicates the lambda at which the coefficients are to be extracted (alternative to specifying 'lambda').
...	Other parameters of underlying basic functions.

Value

A vector or matrix with the estimated coefficients.

Examples

n <- 100
p <- 12
nr <- 4
g <- paste0("Group ",ceiling(1:p / nr))
X <- matrix(rnorm(n * p), n, p)
b <- c(-3:3)
y_lin <- X[, 1:length(b)] %*% b + 5 * rnorm(n)
y_log <- rbinom(n, 1, exp(y_lin) / (1 + exp(y_lin)))

lin_fit <- sgp.cv(X, y_lin, g, type = "linear")
coef(lin_fit)

log_fit <- sgp.cv(X, y_log, g, type = "logit")
coef(log_fit)

SGPR documentation built on May 29, 2024, 5:27 a.m.