l2_balance_internal: Re-weight data to a target with local and global constraints

In ebenmichael/balancer: Matrix constraints for covariate balance

Re-weight data to a target with local and global constraints

Description

Re-weight data to a target with local and global constraints

Usage

l2_balance_internal(
  Xz,
  targetz,
  lambda = 0,
  lowlim = 0,
  uplim = 1,
  scale_sample_size = T,
  exact_global = T,
  target_propz = NULL,
  verbose = TRUE,
  eps_abs = 1e-05,
  eps_rel = 1e-05,
  ...
)

Arguments

Xz	length J list of n_j x d matrix of covariates for each group j
targetz	length J list of d-dimensional vectors of targets for each group j
lambda	Regularization hyper parameter, default 0
lowlim	Lower limit on weights, default 0
uplim	Upper limit on weights, default 1
scale_sample_size	Whether to scale the dispersion penalty by the sample size of each group, default T
exact_global	Whether to enforce exact balance for overall population
target_propz	J-dimensional vector of group proportions in the target population, must not be NULL if exact_global is TRUE
verbose	Whether to show messages, default T
eps_abs	Absolute error tolerance for solver
eps_rel	Relative error tolerance for solver
...	Extra arguments for osqp solver

Value

vector of weights solving balancing optimization problem

ebenmichael/balancer documentation built on Jan. 17, 2024, 2:56 p.m.