grouplasso_logreg_grid | R Documentation |
Fit grouplasso logistic regression estimator over a grid of lambda values
grouplasso_logreg_grid( Y, X, groups, n.lambda, lambda.min.ratio, lambda.max.ratio = 1, w, tol = 1e-04, maxiter = 500, report.prog = FALSE )
Y |
the binary response vector |
X |
matrix containing the design matrices |
groups |
a vector indicating to which group each covariate belongs |
n.lambda |
the number of lambda values desired |
lambda.min.ratio |
ratio of the smallest lambda value to the smallest value of lambda which admits no variables to the model |
lambda.max.ratio |
ratio of the largest lambda value to the smallest value of lambda which admits no variables to the model |
w |
group-specific weights for different penalization of different groups |
tol |
a convergence criterion |
maxiter |
the maximum allowed number of iterations |
report.prog |
a logical indicating whether the progress of the algorithm should be printed to the console |
a list containing the fits over a grid of lambda values as well as the vector of lambda values
grouplasso_logreg_data <- get_grouplasso_data(n = 400, response = "binary") grouplasso_logreg_grid.out <- grouplasso_logreg_grid(Y = grouplasso_logreg_data$Y, X = grouplasso_logreg_data$X, groups = grouplasso_logreg_data$groups, n.lambda = 25, lambda.min.ratio = 0.001, w = grouplasso_logreg_data$w, tol = 1e-3, maxiter = 500, report.prog = TRUE)
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