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>.


Reference manual

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install.packages("kbal")

0.1.4 by Borna Bateni, 8 months ago


https://github.com/chadhazlett/kbal


Browse source code at https://github.com/cran/kbal


Authors: Chad Hazlett [aut, cph] , Ciara Sterbenz [aut] , Erin Hartman [ctb] , Alex Kravetz [ctb] , Borna Bateni [aut, cre]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp, RcppParallel, dplyr, RSpectra

Linking to Rcpp, RcppParallel


See at CRAN