cv.glmmLasso: Cross Validation for glmmLasso package

In yonicd/lmmen: Linear Mixed Model Elastic Net

Description

Cross Validation for glmmLasso package as shown in example xxx

Usage

cv.glmmLasso(dat, form.fixed = NULL, form.rnd = NULL, lambda = seq(500, 0,
  by = -5), family = stats::gaussian(link = "identity"))

Arguments

dat	data.frame, containing y,X,Z and subject variables
form.fixed	formaula, fixed param formula, Default: NULL
form.rnd	list, named list containing random effect formula, Default: NULL
lambda	numeric, vector containing lasso penalty levels, Default: seq(500, 0, by = -5)
family	family, family function that defines the distribution link of the glmm, Default: gaussian(link = "identity")

Value

list of a fitted glmmLasso object and the cv BIC path

See Also

glmmLasso @references Variable selection for generalized linear mixed models by ell 1-penalized estimation. Statistics and Computing, pages 1–18, 2014.

Examples

## Not run: cv.glmmLasso(initialize_example(seed=1))

yonicd/lmmen documentation built on May 9, 2019, 2:29 p.m.