lagrange: Langrangian Functions for Bregman Distances with Linear...

lagrangeR Documentation

Langrangian Functions for Bregman Distances with Linear Equality Constraints

Description

Use lagrange_ent for the unnormalized relative entropy.

Usage

lagrange_ent(coefs, constraint, target, base_weights)

lagrange_bent(coefs, constraint, target, base_weights)

lagrange_sent(coefs, constraint, target, base_weights)

Arguments

coefs

vector of Lagrangian multipliers (also known as the dual vector).

constraint

a matrix that determines the basis of a linear subspace which define the equality constraints of the optimization problem.

target

the target margins of the linear equality constraints. This vector should have a length equal to the number of columns in constraint.

base_weights

a vector of base weights with length equal to the number of rows in constraint.

Details

Use lagrange_bent for the binary relative entropy.

Use lagrange_sent for the shifted unnormalized relative entropy.


kevjosey/cbal documentation built on July 22, 2023, 11:04 a.m.