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

Description Usage Arguments Details Value

View source: R/splmmControl.R

Definition of various kinds of options in the algorithm.

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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))

`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.