gsbm_mcgd: Fit sparse main effects plus low-rank interactions model with...
In genevievelrobin/gsbm:

Fit sparse main effects plus low-rank interactions model with least-squares data fitting term (numeric variables only)

1 2	gsbm_mcgd(A, lambda1, lambda2, epsilon, U = NULL, maxit = 100, thresh = 1e-06, S0 = NULL, L0 = NULL, R0 = NULL, trace.it = T)

`A`	nxn adjacency matrix
`lambda1`	regularization parameter for nuclear norm penalty (positive number)
`lambda2`	regularization parameter for ell_2,1 penalty (positive number)
`U`	lower bound on nuclear norm (positive number, if NULL, default method is applied)
`maxit`	maximum number of iterations (positive integer)
`thresh`	convergence tolerance (positive number)
`S0`	initial value for the sparse component
`L0`	initial value for the low-rank component
`R0`	lower bound on nuclear norm of L0 (positive number, if NULL, default method is applied)
`trace.it`	whether messages about convergence should be printed (boolean)