R/nonzeroCoef.R

In glmnet: Lasso and Elastic-Net Regularized Generalized Linear Models

nonzeroCoef = function (beta, bystep = FALSE) 
{
### bystep = FALSE means which variables were ever nonzero
### bystep = TRUE means which variables are nonzero for each step
  nr=nrow(beta)
  if (nr == 1) {#degenerate case
    if (bystep) 
      apply(beta, 2, function(x) if (abs(x) > 0) 
            1
      else NULL)
    else {
      if (any(abs(beta) > 0)) 
        1
      else NULL
    }
  }
  else {
    beta=abs(beta)>0 # this is sparse
    which=seq(nr)
    ones=rep(1,ncol(beta))
    nz=as.vector((beta%*%ones)>0)
    which=which[nz]
    if (bystep) {
      if(length(which)>0){
        beta=as.matrix(beta[which,,drop=FALSE])
        nzel = function(x, which) if (any(x)) 
          which[x]
        else NULL
        which=apply(beta, 2, nzel, which)
        if(!is.list(which))which=data.frame(which)# apply can return a matrix!!
        which
      }
      else{
        dn=dimnames(beta)[[2]]
        which=vector("list",length(dn))
        names(which)=dn
        which
      }
        
    }
    else which
  }
}