# splmmControl: Options for the 'splmm' Algorithm In splmm: Simultaneous Penalized Linear Mixed Effects Models

## Description

Definition of various kinds of options in the algorithm.

## Usage

 ```1 2 3``` ```splmmControl(tol=10^(-4),trace=1,maxIter=1000,maxArmijo=20,number=5,a_init=1, delta=0.1,rho=0.001,gamma=0,lower=10^(-6),upper=10^8,seed=532,VarInt=c(0,10), CovInt=c(-5,5),thres=10^(-4)) ```

## Arguments

 `tol` convergence tolerance `trace` integer. 1 prints no output, 2 prints warnings, 3 prints the current function values and warnings (not recommended) `maxIter` maximum number of (outer) iterations `maxArmijo` maximum number of steps to be chosen in the Armijo Rule. If the maximum is reached, the algorithm continues with optimizing the next coordinate. `number` integer. Determines the active set algorithm. The zero fixed-effects coefficients are only updated each number iteration. It may be that a smaller number increases the speed of the algorithm. Use 0 ≤ number ≤ 5. `a_init` α_{init} in the Armijo step. See Schelldorfer et. al. (2010). `delta` δ in the Armijo step. See Schelldorfer et. al. (2010) `rho` ρ in the Armijo step. See Schelldorfer et. al. (2010) `gamma` γ in the Armijo step. See Schelldorfer et. al. (2010) `lower` lower bound for the Hessian `upper` upper bound for the Hessian `seed` set.seed for calculating the starting value, which performs a 10-fold cross-validation. `VarInt` Only for opt="optimize". The interval for the variance parameters used in "optimize". See help("optimize") `CovInt` Only for opt="optimize". The interval for the covariance parameters used in "optimize". See help("optimize") `thres` If a variance or covariance parameter has smaller absolute value than thres, the parameter is set to exactly zero.

## Details

For the Armijo step parameters, see Bertsekas (2003)

## Value

Exactly the same as `arguments`.

splmm documentation built on Sept. 8, 2021, 5:08 p.m.