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20142026
most citedThe Horseshoe Estimator: Posterior Concentration around Nearly Black Vectors

107 citations · 160 across the 9 of their papers we have counts for

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9 papers · 1 filter

math.ST2023

Bayesian sensitivity analysis for a missing data model

Bart Eggen, Stéphanie L. van der Pas, Aad W. van der Vaart

In causal inference, sensitivity analysis is important to assess the robustness of study conclusions to key assumptions. We perform sensitivity analysis of the assumption that miss…

math.ST2023

Asymptotics of Caliper Matching Estimators for Average Treatment Effects

Máté Kormos, Stéphanie van der Pas, Aad van der Vaart

Caliper matching is used to estimate causal effects of a binary treatment from observational data by comparing matched treated and control units. Units are matched when their prope…

math.ST2020

Multiscale Bayesian Survival Analysis

Ismaël Castillo, Stéphanie van der Pas

We consider Bayesian nonparametric inference in the right-censoring survival model, where modeling is made at the level of the hazard rate. We derive posterior limiting distributio…

math.ST2017

Posterior Concentration for Bayesian Regression Trees and Forests

Veronika Rockova, Stephanie van der Pas

Since their inception in the 1980's, regression trees have been one of the more widely used non-parametric prediction methods. Tree-structured methods yield a histogram reconstruct…

math.ST2016

Bayesian Community Detection

Stéphanie van der Pas, Aad van der Vaart

We introduce a Bayesian estimator of the underlying class structure in the stochastic block model, when the number of classes is known. The estimator is the posterior mode correspo…

math.ST2016★ 1 cited

Uncertainty quantification for the horseshoe

Stéphanie van der Pas, Botond Szabó, Aad van der Vaart

We investigate the credible sets and marginal credible intervals resulting from the horseshoe prior in the sparse multivariate normal means model. We do so in an adaptive setting w…

math.ST2015★ 40 cited

Conditions for Posterior Contraction in the Sparse Normal Means Problem

Stéphanie van der Pas, Jean-Bernard Salomond, Johannes Schmidt-Hieber

The first Bayesian results for the sparse normal means problem were proven for spike-and-slab priors. However, these priors are less convenient from a computational point of view.…

math.ST2014

Almost the Best of Three Worlds: Risk, Consistency and Optional Stopping for the Switch Criterion in Nested Model Selection

Stéphanie van der Pas, Peter Grünwald

We study the switch distribution, introduced by Van Erven et al. (2012), applied to model selection and subsequent estimation. While switching was known to be strongly consistent,…

math.ST2014★ 107 cited

The Horseshoe Estimator: Posterior Concentration around Nearly Black Vectors

S. L. van der Pas, B. J. K. Kleijn, A. W. van der Vaart

We consider the horseshoe estimator due to Carvalho, Polson and Scott (2010) for the multivariate normal mean model in the situation that the mean vector is sparse in the nearly bl…