create.sgldata: Create a sgldata object
In sglOptim: Sparse group lasso generic optimizer

Creates a sgldata object from a design matrix and an optional response vector or matrix.

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create.sgldata(x, y, weights = NULL, sampleGrouping = NULL,
  group.names = NULL, sparseX = is(x, "sparseMatrix"), sparseY = is(y,
  "sparseMatrix"))

`x`	the design matrix, a matrix of size N \times p (will be parsed to the loss module as `X`).
`y`	the responses, `NULL`, a vector or a matrix (will be parsed to the loss module as `Y`)..
`weights`	sample weights, a vector of length N (will be parsed to the loss module as `W`).
`sampleGrouping`	grouping of samples, a factor of length N (will be parsed to the loss module as `G`). Default is no grouping (NULL), that is all samples is the same group.
`group.names`	a vector with the names of the parameter groups (the length must equal the number of rows in the β matrix).
`sparseX`	if TRUE `x` will be treated as sparse, if FALSE `x` will be treated as dens.
`sparseY`	if TRUE `y` will be treated as sparse, if FALSE `y` will be treated as dens.