231 citations · 963 across the 14 of their papers we have counts for
14 papers
Bayesian tolerance regions with an application to linear mixed models
X. Gregory Chen, Aad van der Vaart
We review and contrast frequentist and Bayesian definitions of tolerance regions. We give conditions under which for large samples a Bayesian region also has frequentist validity,…
Incorporating prior information and borrowing information in high-dimensional sparse regression using the horseshoe and variational Bayes
Gino B. Kpogbezan, Mark A. van de Wiel, Wessel N. van Wieringen +1
We introduce a sparse high-dimensional regression approach that can incorporate prior information on the regression parameters and can borrow information across a set of similar da…
Semiparametric Bayesian causal inference
Kolyan Ray, Aad van der Vaart
We develop a semiparametric Bayesian approach for estimating the mean response in a missing data model with binary outcomes and a nonparametrically modelled propensity score. Equiv…
Consistent Estimation in General Sublinear Preferential Attachment Trees
Fengnan Gao, Aad van der Vaart, Rui Castro +1
We propose an empirical estimator of the preferential attachment function in the setting of general preferential attachment trees. Using a supercritical continuous-time branchi…
Higher Order Tangent Spaces and Influence Functions
Aad van der Vaart
We review higher order tangent spaces and influence functions and their use to construct minimax efficient estimators for parameters in high-dimensional semiparametric models.
Needles and Straw in a Haystack: Posterior concentration for possibly sparse sequences
Ismaël Castillo, Aad van der Vaart
We consider full Bayesian inference in the multivariate normal mean model in the situation that the mean vector is sparse. The prior distribution on the vector of means is construc…