View source: R/CPGLIB_Coefficient_Functions.R
coef.CPGLIB | R Documentation |
coef.CPGLIB
returns the coefficients for a CPGLIB object.
## S3 method for class 'CPGLIB' coef(object, groups = NULL, ensemble_average = FALSE, ...)
object |
An object of class 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. |
The coefficients for the CPGLIB object.
Anthony-Alexander Christidis, anthony.christidis@stat.ubc.ca
cpg
# 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) # CPGLIB - Multiple Groups cpg.out <- cpg(x.train, y.train, glm_type="Logistic", G=5, include_intercept=TRUE, alpha_s=3/4, alpha_d=1, lambda_sparsity=0.01, lambda_diversity=1, tolerance=1e-5, max_iter=1e5) # Coefficients for each group cpg.coef <- coef(cpg.out, ensemble_average = FALSE)
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