kbal: Kernel Balancing
Provides a weighting approach that employs kernels to make one group have a similar distribution to another group on covariates. This method matches not only means or marginal distributions but also higher-order transformations implied by the choice of kernel. 'kbal' is applicable to both treatment effect estimation and survey reweighting problems. Based on Hazlett, C. (2020) "Kernel Balancing: A flexible non-parametric weighting procedure for estimating causal effects." Statistica Sinica. <https://www.researchgate.net/publication/299013953_Kernel_Balancing_A_flexible_non-parametric_weighting_procedure_for_estimating_causal_effects>.
| Version: | 0.1.3 |
| Depends: | R (≥ 3.5.0) |
| Imports: | Rcpp (≥ 0.11.0),RcppParallel (≥ 4.4.4),dplyr,RSpectra |
| LinkingTo: | Rcpp,RcppParallel |
| Published: | 2025-07-06 |
| DOI: | 10.32614/CRAN.package.kbal |
| Author: | Chad Hazlett [aut, cph], Ciara Sterbenz [aut], Erin Hartman [ctb], Alex Kravetz [ctb], Borna Bateni [aut, cre] |
| Maintainer: | Borna Bateni <borna at ucla.edu> |
| License: | GPL-2 |GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://github.com/chadhazlett/kbal |
| NeedsCompilation: | yes |
| Materials: | NEWS |
| CRAN checks: | kbal results |
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