A weighting approach the employs kernels to make one group have a similar distribution to another group on covariates not only in terms of means or marginal distributions, but also on higher order transformations implied by the choice of kernel. This applies to both treatment effect estimation and to 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>
Package details |
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Maintainer | Chad Hazlett <chazlett@ucla.edu> |
License | GPL (>=2) |
Version | 0.1 |
URL | https://github.com/chadhazlett/kbal |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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