constraint.box: Create a box constraint for a group.

In adelie: Group Lasso and Elastic Net Solver for Generalized Linear Models

Create a box constraint for a group.

Description

A box constraint sets upper and lower bounds for coefficients in a model. This is done per group, and this function is used separately to set the bounds for each group in the model. The constraints are returned as a list, with number of elements the number of groups. List entries can be NULL, which means no constraints for that group. Currently works with single-response models (so glm.multinomial and glm.multigaussian are excluded). Note that for each group for which non-null constraints are provide, a separate call to constraint.box() must be made (i.e. the constraint object cannot be replicated). See the second example below.

Usage

constraint.box(lower, upper, max_iters = 100, tol = 1e-09)

Arguments

lower	lower bound for each coefficient in the group. If the group has m variables, this should be a vector of length m. Values can be -Inf.
upper	upper bound for each coefficient in the group. If the group has m variables, this should be a vector of length m. Values can be Inf.
max_iters	maximum number of proximal Newton iterations; default is 100.
tol	convergence tolerance for proximal Newton; default is 1e-9.

Value

Box constraint object.

Author(s)

Trevor Hastie and James Yang
Maintainer: Trevor Hastie [e-mail]

Examples

# Group of length 10, with positivity constraint on all the coefficients.
lower <- rep(0,10)
upper <- rep(Inf,10)
cont <- constraint.box(lower = lower, upper = upper)

# 10 singleton groups, and non-negativity constraints on all parameters.
cont <- lapply(1:10, function(i)constraint.box(lower = 0, upper = Inf))

# Same as above, but non-negativity constraints only on first 5 parameters.
cont <- lapply(1:5, function(i)constraint.box(lower = 0, upper = Inf))
cont <- c(cont, rep(list(NULL), 5)) # rep rule does not apply to NULL

adelie documentation built on April 3, 2025, 8:58 p.m.