prepare.args: Generic function for preparing the sgl call arguments
Description
Compute and prepare the sgl call arguments for the
objective function
$$\mathrm{loss}(\mathrm{data})(\beta) + \lambda
\left( (1-\alpha) \sum_{J=1}^m \gamma_J \|\beta^{(J)}\|_2
+ \alpha \sum_{i=1}^{n} \xi_i |\beta_i| \right)$$ where
$\mathrm{loss}$ is a loss/objective function. The
$n$ parameters are organized in the parameter matrix
$\beta$ with dimension $q\times p$. The vector
$\beta^{(J)}$ denotes the $J$ parameter group,
the dimension of $\beta^{(J)}$ is denote by
$d_J$. The dimensions $d_J$ must be multiple of
$q$, and $\beta = (\beta^{(1)} \cdots
\beta^{(m)})$. The group weights $\gamma \in
[0,\infty)^m$ and the parameter weights $\xi \in
[0,\infty)^{qp}$.
Usage
prepare.args(data, ...)
Arguments
data
a data object
...
additional parameters
Value
block.dima vector of length $m$, containing
the dimensions $d_J$ of the groups (i.e. the number
of parameters in the groups)
groupWeightsa
vector of length $m$, containing the group weights
parameterWeightsa matrix of dimension $q
\times p$, containing the parameter weights
alphathe $\alpha$ value
datathe data
parsed to the loss module
group.orderoriginal
order of the columns of $\beta$. Before sgl routines
return $\beta$ will be reorganized according to this
order.