standardize_indirect: Re-weight populations to group targets

In ebenmichael/balancer: Matrix constraints for covariate balance

Re-weight populations to group targets

Description

Re-weight populations to group targets

Usage

standardize_indirect(
  X,
  Z,
  lambda = 0,
  lowlim = 0,
  uplim = 1,
  scale_sample_size = F,
  verbose = TRUE,
  n_cores = 1,
  eps_abs = 1e-05,
  eps_rel = 1e-05,
  ...
)

Arguments

X	n x d matrix of covariates
Z	Vector of group indicators with J levels
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
verbose	Whether to show messages, default T
n_cores	Number of cores to find weights in parallel
eps_abs	Absolute error tolerance for solver
eps_rel	Relative error tolerance for solver
...	Extra arguments for osqp solver

Value

• weights Estimated weights as an n x J matrix

• imbalance Imbalance in covariates as a d X J matrix

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