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

In dewittpe/cbal-v1: Covariate Balancing Weights using Generalized Projections of Bregman Distances

Description

Use lagrange_ent for the unnormalized relative entropy.

Usage

lagrange_ent(coefs, cmat, target, base_weights)

lagrange_bent(coefs, cmat, target, base_weights)

lagrange_sent(coefs, cmat, target, base_weights)

Arguments

coefs	vector of Lagrangian multipliers.
cmat	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 cmat.
base_weights	a vector of sampling weights with length equal to the number of rows in cmat.

Details

Use lagrange_bent for the binary relative entropy.

Use lagrange_sent for the shifted unnormalized relative entropy.

dewittpe/cbal-v1 documentation built on July 2, 2020, 6:24 p.m.