listToMatrix: Obtain a sparse matrix of the coefficients of the path
In MLGL: Multi-Layer Group-Lasso

Description Usage Arguments Details Value See Also Examples

Obtain a sparse matrix of the coefficients of the path

1	listToMatrix(x, row = c("covariates", "lambda"))

`x`	`MLGL` object
`row`	"lambda" or "covariates". If row="covariates", each row of the output matrix represents a covariates else ff row="lambda", it represents a value of lambda.

This functions can be used with a MLGL object to obtain a matrix with all estimated coefficients for the p original variables. In case of overlapping groups, coefficients from repeated variables are summed.

a sparse matrix containing the estimated coefficients for different values of lambda

MLGL, overlapgglasso

# Simulate gaussian data with block-diagonal variance matrix containing 12 blocks of size 5
X <- simuBlockGaussian(50, 12, 5, 0.7)
# Generate a response variable
y <- X[,c(2,7,12)]%*%c(2,2,-2) + rnorm(50,0,0.5)
# Apply MLGL method
res <- MLGL(X,y)
# Convert output in sparse matrix format
beta <- listToMatrix(res)