linear: Linear Constraint

In holiglm: Holistic Generalized Linear Models

Linear Constraint

Description

Linear Constraint

Usage

linear(L, dir, rhs, on_big_m = FALSE)

Arguments

L	a named vector or matrix defining the linear constraints on the coefficients of the covariates.
dir	a character vector giving the direction of the linear constraints.
rhs	a numeric vector giving the right hand side of the linear constraint.
on_big_m	a logical indicating if the constraint should be imposed on the big-M related binary variables.

Value

A holistic generalized model constraint, object inheriting from class "hglmc".

References

Lawson, C. L., & Hanson, R. J. (1995). Solving least squares problems. Society for Industrial and Applied Mathematics. Society for Industrial and Applied Mathematics. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1137/1.9781611971217")}

See Also

Other Constraint-Constructors: group_equal(), group_inout(), group_sparsity(), include(), k_max(), lower(), pairwise_sign_coherence(), rho_max(), sign_coherence(), upper()

Examples

# vector constraint
beta <- c(1, -2, 3)
dat <- rhglm(100, beta)
constraints <- c(linear(c(x1 = 2, x2 = 1), "==", 0), rho_max(1))
hglm(y ~ ., data = dat, constraints = constraints)

# matrix constraint
dat <- rhglm(100, c(1, -2, 3, 4, 5, 6, 7))
mat <- diag(2)
colnames(mat) <- c("x1", "x5")
constraints <- c(linear(mat, c("==", "=="), c(-1, 3)), rho_max(1))
hglm(y ~ ., data = dat, constraints = constraints)

holiglm documentation built on April 3, 2025, 7:09 p.m.