ericdunipace/causalOT: Optimal Transport Weights for Causal Inference

Uses optimal transport distances to find probabilistic matching estimators for causal inference. These methods are described in Dunipace, Eric (2021) <arXiv:2109.01991>. The package will build the weights, estimate treatment effects, and calculate confidence intervals via the methods described in the paper. The package also supports several other methods as described in the help files.

install.packages("remotes")
remotes::install_github("ericdunipace/causalOT")