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10 papers · 1 filter

stat.ME2026

Local graph estimation with pathwise false discovery control

Omar Melikechi, David B. Dunson, Noureddine Melikechi +1

Many datasets include a small set of variables, such as biomarkers or clinical outcomes, whose relationships to the broader system are of primary scientific interest. Estimating th…

stat.ME2026

Spectral decomposition-assisted multi-study factor analysis

Lorenzo Mauri, Niccolò Anceschi, David B. Dunson

This article focuses on covariance estimation for multi-study data. Popular approaches employ factor-analytic terms with shared and study-specific loadings that decompose the varia…

stat.ME2025

Blessing of dimension in Bayesian inference on covariance matrices

Shounak Chattopadhyay, Anru R. Zhang, David B. Dunson

Bayesian factor analysis is routinely used for dimensionality reduction in modeling of high-dimensional covariance matrices. Factor analytic decompositions express the covariance a…

stat.ME2025

Link prediction in ecological networks under extreme taxonomic bias

Jennifer N. Kampe, Camille M. M. DeSisto, David B. Dunson

Ecological networks offer powerful insights into community function, but without first characterizing these networks accurately, our ability to detect and interpret changes under e…

stat.ME2025

Nonparametric predictive inference for discrete data via Metropolis-adjusted Dirichlet sequences

Davide Agnoletto, Tommaso Rigon, David B. Dunson

This article is motivated by challenges in conducting Bayesian inferences on unknown discrete distributions, with a particular focus on count data. To avoid the computational disad…

stat.ME2025

Sequential Gibbs Posteriors with Applications to Principal Component Analysis

Steven Winter, Omar Melikechi, David B. Dunson

Gibbs posteriors are proportional to a prior distribution multiplied by an exponentiated loss function, with a key tuning parameter weighting information in the loss relative to th…