Nothing
DMRnet4glm <- function(X, y, clust.method, o, nlambda, lam, maxp, lambda) {
y <- prelasso_binomial(y)
out <- prelasso_common(X, y)
n <- out$n
levels.listed <- out$levels.listed
fl <- out$fl
x.full <- out$x.full_normalized
p <- out$p
p.x <- out$p.x
ord <- out$ord
groups <- out$groups
X <- out$X
if (is.null(lambda)) {
user.lambda<-substitute() #make user.lambda - paradoxically - not present in a call to grpreg
} else {
nlambda <- length(lambda) #override this parameter
user.lambda <- lambda
}
mL <- grpreg::grpreg(x.full[,-1, drop=FALSE], y, group=groups, penalty = "grLasso", family ="binomial", nlambda = nlambda, lambda = user.lambda)
bb <- postlasso_common(mL$lambda, n, mL$beta)
fac <- postlasso_fac(bb, groups) #fac must be computed on bb without intercept, it happens internally in postlasso_fac()
SS <- postlasso_O_step_preparation(p, p.x, n, o, fac, interc=TRUE)
mm <- lapply(1:ncol(SS), function(i) DMRnet4glm_help(SS[,i], X, y, fl, clust.method = clust.method, lam = lam))
return(wrap_up_binomial(mm, p, maxp, SS, fl, x.full, ord, n, levels.listed, mL, list(family = "binomial", clust.method = clust.method, o = o, nlambda = nlambda, lam = lam, maxp = maxp, lambda = lambda)))
}
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