Book of Donmon Teith

Bayesian Nonparametric Methods for Missing Data and Causal Inference provides an overview of flexible Bayesian nonparametric (BNP) methods for modeling joint or

Bayesian Nonparametrics for Causal Inference and Missing Data provides an overview of flexible Bayesian nonparametric (BNP) methods for modeling joint or condit

Bayesian nonparametrics works - theoretically, computationally. The theory provides highly flexible models whose complexity grows appropriately with the amount

As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Ba

This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.