# golden_section_2d: Golden section two dimensional grid search on L1 lmmen... In lmmen: Linear Mixed Model Elastic Net

## Description

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

## Usage

 ```1 2 3``` ```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

 ```1 2 3 4 5``` ```## 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) ## End(Not run) ```

lmmen documentation built on Aug. 15, 2017, 1:02 a.m.