lam.max.hsm: Computes the smallest lam value such that beta = 0.

In hsm: A Path-Based BCD for Proximal Function of Latent Group Lasso

Description

Computes lammax, the smallest value of lam for which hsm gives a completely sparse solution.

Usage

lam.max.hsm(y, assign, w.assign)

Arguments

y	Length-p vector used in proximal operator.
assign	Matrix of p columns that gives the assignments of variables over different path graphs. Each row of assign corresponds to a path graph decomposed from DAG. Refer to paths for more details.
w.assign	List of length nrow(assign), for which the lth element contains the weights corresponding to the lth row of assign (the lth path graph). For example, if the lth path graph is made up of three nodes indexed with {3, 4, 6, 8}, w.assign[[l]] = {w_3, w_4, w_6, w_8}. Refer to paths for more details.

See Also

hsm.path

hsm documentation built on May 2, 2019, 7:24 a.m.