`causalTransportR`

implements a number of estimators to generalize and transport causal effects by reweighting doubly-robust score functions with transformations of selection scores. All nuisance functions are cross-fit using fast supervised learning algorithms.

## Estimators

The `ateGT`

function implements the following estimators by aggregating estimates of individual marginal means over different marginal *X* distributions for the generalization and transportation case. *μ*, *π*, *ρ* are nuisance parameters fit using ML.

## Installation

```
# install.packages("remotes") # if remotes isn't installed
remotes::install_github("Netflix-Skunkworks/causalTransportR")
```