Obtain a sparse matrix of the coefficients of the path
"lambda" or "covariates". If row="covariates", each row of the output matrix represents a covariate else if row="lambda", it represents a value of lambda.
This function 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 lambdas
1 2 3 4 5 6 7 8
# 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)
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