lmmen (version 1.0)

golden_section_2d: Golden section two dimensional grid search on L1 lmmen penalties

Description

Solve for local minimum with two dimensional golden section on L1 lmmen penalties.

Usage

golden_section_2d(dat, init.beta, l2 = c(1, 1), opt.lb = c(0, 0),
  opt.ub = c(1, 1), opt.maxiter = 100, opt.tol = 0.1, opt.tau = (sqrt(5)
  - 1)/2)

Arguments

dat

matrix, matrix that includes y (response),X (population covariates), Z (random effects covariates (not incl random intercept))

init.beta

numeric, initial fixed effects estimates

l2

numeric, L2 penalty levels Default: c(1, 1)

opt.lb

numeric, start of interval for L1 fixed and L1 random effects, Default: c(0, 0)

opt.ub

numeric, end of interval for L1 fixed and L1 random effects Default: c(1, 1)

opt.maxiter

numeric, maximum iterations to search, Default: 100

opt.tol

numeric, accuracy value, Default: 0.1

opt.tau

numeric, golden proportion coefficient (~0.618) Default: (sqrt(5) - 1)/2

Value

lmmen list object inluding lmmen fit object of min BIC solution and summary statistics from the grid search

Examples

# NOT RUN {
 dat <- initialize_example(n.i = 5,n = 30,q=4,seed=1)
 init <- init.beta(dat,method='glmnet')
 golden_section_2d(dat,init)
# }