perf.enet: cross-validation function for elastic net panel

In singha53/amritr: Accessory Functions Used by Amrit Singh

Description

Estimate test error of elastic net panel

Usage

perf.enet(object, validation = c("Mfold", "loo"), M = 5, iter = 10,
  threads = 4, progressBar = TRUE)

Arguments

M	= # of folds
iter	= number of times to repeat cross-valiation
threads	- number of cpus (each cross-valiation scheme performed on a separate node)
progressBar	- show progressbar (TRUE/FALE)
X	nxp matrix - training dataset
Y	categorical variables
alpha	= 1 (lasso), alpha = 0 (ridge), 0 < alpha < 1 (elastic net penalty)
family	"binomial" or "multinomial"
lambda	= strength of elastic net penalty

singha53/amritr documentation built on July 21, 2019, 3:46 p.m.