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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>.
Getting started
Browse package contents
Package details |
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| Author | Chad Hazlett [aut, cph], Ciara Sterbenz [aut], Erin Hartman [ctb], Alex Kravetz [ctb], Borna Bateni [aut, cre] |
| Maintainer | Borna Bateni <borna@ucla.edu> |
| License | GPL (>= 2) |
| Version | 0.1.2 |
| URL | https://github.com/chadhazlett/kbal |
| Package repository | View on CRAN |
| Installation |
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