Bayesian Nonparametrics For Causal Inference And Missing Data

Bayesian nonparametric BNP methods can be used to flexibly model joint or conditional distributions as well as functional relationships. These methods along with causal andor missingness assumptions can be used with the gformula to infer causal effects.