doi:10.1080/01621459.2015.1023805>. The degree of balance can be specified for each covariate. In addition, sampling weights can be estimated that allow a sample to generalize to a population specified with given target moments of covariates.">

optweight: Optimization-Based Stable Balancing Weights (original) (raw)

Use optimization to estimate weights that balance covariates for binary, multi-category, continuous, and multivariate treatments in the spirit of Zubizarreta (2015) <doi:10.1080/01621459.2015.1023805>. The degree of balance can be specified for each covariate. In addition, sampling weights can be estimated that allow a sample to generalize to a population specified with given target moments of covariates.

Version: 1.0.0
Depends: R (≥ 4.1.0)
Imports: osqp (≥ 0.6.3.3), chk (≥ 0.10.0), rlang (≥ 1.1.6), Matrix (≥ 1.2-13), ggplot2 (≥ 3.5.0), graphics, stats, utils
Suggests: cobalt (≥ 4.6.0), scs (≥ 3.2.7), clarabel (≥ 0.10.1), highs (≥ 1.10.0-3), lpSolve (≥ 5.6.23), WeightIt, gbm, marginaleffects, sandwich, fwb, knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2025-09-09
DOI: 10.32614/CRAN.package.optweight
Author: Noah Greifer ORCID iD [aut, cre]
Maintainer: Noah Greifer <noah.greifer at gmail.com>
BugReports: https://github.com/ngreifer/optweight/issues
License: GPL-2 | GPL-3 [expanded from: GPL]
URL: https://ngreifer.github.io/optweight/,https://github.com/ngreifer/optweight
NeedsCompilation: no
Materials: README, NEWS
In views: CausalInference
CRAN checks: optweight results

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