coef.cv.CPGLIB {CPGLIB} | R Documentation |
Coefficients for cv.CPGLIB Object
Description
coef.cv.CPGLIB
returns the coefficients for a cv.CPGLIB object.
Usage
## S3 method for class 'cv.CPGLIB'
coef(object, groups = NULL, ensemble_average = FALSE, ...)
Arguments
object |
An object of class cv.CPGLIB. |
groups |
The groups in the ensemble for the coefficients. Default is all of the groups in the ensemble. |
ensemble_average |
Option to return the average of the coefficients over all the groups in the ensemble. Default is FALSE. |
... |
Additional arguments for compatibility. |
Value
The coefficients for the cv.CPGLIB object. Default is FALSE.
Author(s)
Anthony-Alexander Christidis, anthony.christidis@stat.ubc.ca
See Also
Examples
# Data simulation
set.seed(1)
n <- 50
N <- 2000
p <- 300
beta.active <- c(abs(runif(p, 0, 1/2))*(-1)^rbinom(p, 1, 0.3))
# Parameters
p.active <- 150
beta <- c(beta.active[1:p.active], rep(0, p-p.active))
Sigma <- matrix(0, p, p)
Sigma[1:p.active, 1:p.active] <- 0.5
diag(Sigma) <- 1
# Train data
x.train <- mvnfast::rmvn(n, mu = rep(0, p), sigma = Sigma)
prob.train <- exp(x.train %*% beta)/
(1+exp(x.train %*% beta))
y.train <- rbinom(n, 1, prob.train)
# Test data
x.test <- mvnfast::rmvn(N, mu = rep(0, p), sigma = Sigma)
prob.test <- exp(x.test %*% beta)/
(1+exp(x.test %*% beta))
y.test <- rbinom(N, 1, prob.test)
mean(y.test)
# CV CPGLIB - Multiple Groups
cpg.out <- cv.cpg(x.train, y.train,
glm_type = "Logistic",
G = 5, include_intercept = TRUE,
alpha_s = 3/4, alpha_d = 1,
n_lambda_sparsity = 100, n_lambda_diversity = 100,
tolerance = 1e-5, max_iter = 1e5)
cpg.coef <- coef(cpg.out)
# Coefficients for each group
cpg.coef <- coef(cpg.out, ensemble_average = FALSE)
[Package CPGLIB version 1.1.1 Index]