Usage
lmmlassoControl(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
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 $0 \le number \le 5$.
a_init
$\alpha_{init}$ in the Armijo step. See Schelldorfer et. al. (2010).
delta
$\delta$ in the Armijo step. See Schelldorfer et. al. (2010)
rho
$\rho$ in the Armijo step. See Schelldorfer et. al. (2010)
gamma
$\gamma$ 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.