56 citations · 71 across the 19 of their papers we have counts for
4 papers · 1 filter
Density Regression with Bayesian Additive Regression Trees
Vittorio Orlandi, Jared Murray, Antonio Linero +1
Flexibly modeling how an entire density changes with covariates is an important but challenging generalization of mean and quantile regression. While existing methods for density r…
In Nonparametric and High-Dimensional Models, Bayesian Ignorability is an Informative Prior
Antonio R. Linero
In problems with large amounts of missing data one must model two distinct data generating processes: the outcome process which generates the response and the missing data mechanis…
Causal Mediation and Sensitivity Analysis for Mixed-Scale Data
Lexi Rene, Antonio R. Linero, Elizabeth Slate
The goal of causal mediation analysis, often described within the potential outcomes framework, is to decompose the effect of an exposure on an outcome of interest along different…
The How and Why of Bayesian Nonparametric Causal Inference
Antonio R. Linero, Joseph L. Antonelli
Spurred on by recent successes in causal inference competitions, Bayesian nonparametric (and high-dimensional) methods have recently seen increased attention in the causal inferenc…