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/stats>.
| Version: |
0.1.1 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
Rcpp (≥ 0.11.0), RcppParallel (≥ 4.4.4), dplyr, RSpectra |
| LinkingTo: |
Rcpp, RcppParallel |
| Published: |
2024-10-16 |
| 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 |
Documentation:
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