4 papers · 1 filter
E-Values For Multiplicity Control In Multiverse Analysis
Paul Rognon-Vael, David Rossell
Multiverse analysis refers to a common situation where one wishes to assess the association between multiple possible treatment definitions and multiple possible outcome definition…
Positive-definiteness in separable priors: effects on prior interpretability and inference
Jack Storror Carter, David Rossell
A popular class of priors for symmetric positive-definite matrices assumes independent entries and adds a truncation to ensure positive-definiteness. While conceptually simple and…
Empirical Bayes for Data Integration
Paul Rognon-Vael, David Rossell
We discuss the use of empirical Bayes for data integration, in the sense of transfer learning. Our main interest is in settings where one wishes to learn structure (e.g. feature se…
Bayesian computation for high-dimensional Gaussian Graphical Models with spike-and-slab priors
Deborah Sulem, Jack Jewson, David Rossell
Gaussian graphical models are widely used to infer dependence structures. Bayesian methods are appealing to quantify uncertainty associated with structural learning, i.e., the plau…