7 papers
Shrinkage through multiple identifiability
Carlos GarcÃa Meixide, David RÃos Insua
We propose an empirical Bayes framework for combining estimators obtained from multiple identification functionals associated with the same estimand. We adaptively pool a collectio…
Causal inference via implied interventions
Carlos GarcÃa Meixide, Mark J. van der Laan
In the context of having an instrumental variable, the standard practice in causal inference begins by targeting an effect of interest and proceeds by formulating assumptions enabl…
Highly Adaptive Empirical Risk Minimization with Principal Components
Carlos GarcÃa Meixide, Mingxun Wang, Alejandro Schuler +1
The Highly Adaptive Lasso (HAL) delivers unprecedented guarantees in nonparametric minimum loss estimation under minimal smoothness assumptions, such as dimension-free minimax opti…
Predictive posteriors under hidden confounding
Carlos GarcÃa Meixide, David RÃos Insua
Predicting outcomes in external domains is challenging due to hidden confounders that potentially influence both predictors and outcomes. Well-established methods frequently rely o…
Covariance as a commutator
Carlos GarcÃa Meixide
The covariance between real finite variance random variables can be expressed as the commutator of taking expectations and multiplying, both viewed as operators extended to act joi…
Uncertainty quantification for intervals
Carlos GarcÃa Meixide, Michael R. Kosorok, Marcos Matabuena
Data following an interval structure are increasingly prevalent in many scientific applications. In medicine, clinical events are often monitored between two clinical visits, makin…