linear function

Linear Constraint

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.

Returns

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

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)

References

Lawson, C. L., & Hanson, R. J. (1995). Solving least squares problems. Society for Industrial and Applied Mathematics. Society for Industrial and Applied Mathematics. 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()