features.lsgl: Nonzero Features

In nielsrhansen/lsgl: Multivariate Linear Sparse Group Lasso

Nonzero Features

Description

Extracts the nonzero features for each model.

Usage

## S3 method for class 'lsgl'
features(object, ...)

Arguments

object	a lsgl object
...	ignored

Value

a list of of length nmod(x) containing the nonzero features (that is nonzero columns of the beta matrices)

Author(s)

Martin Vincent

Examples

set.seed(100) # This may be removed, it ensures consistency of the daily tests

## Simulate from Y=XB+E, the dimension of Y is N x K, X is N x p, B is p x K

N <- 100 #number of samples
p <- 50 #number of covariates
K <- 25  #number of groups

B<-matrix(sample(c(rep(1,p*K*0.1),rep(0, p*K-as.integer(p*K*0.1)))),nrow=p,ncol=K)

X<-matrix(rnorm(N*p,1,1),nrow=N,ncol=p)
Y<-X%*%B+matrix(rnorm(N*K,0,1),N,K)

lambda<-lsgl::lambda(X,Y, alpha=1, d = 25, lambda.min=.5, intercept=FALSE)
fit <-lsgl::fit(X,Y, alpha=1, lambda = lambda, intercept=FALSE)

# the nonzero features of model 1, 10 and 25
features(fit)[c(1,10,25)]

# count the number of nonzero features in each model
sapply(features(fit), length)

nielsrhansen/lsgl documentation built on Feb. 11, 2024, 8:07 a.m.