24 papers
Bayesian inference on beta diversity via feature allocation models with imperfect detection
Federica Stolf, Tommaso Rigon, David B. Dunson
Beta diversity quantifies variation in species composition across ecological communities and is fundamental for understanding biodiversity patterns across space and environmental g…
Overfitted high-dimensional matrix factorizations via adaptive spectral shrinkage
Lorenzo Mauri, David B. Dunson
Factor models are popular approaches for analyzing high-dimensional data to extract low-rank signals and estimate covariances. They decompose the covariance matrix as the sum of lo…
Bayesian modeling of multi-species labeling errors in ecological studies
Haoxuan Wang, Patrik Lauha, David B. Dunson
Ecological and conservation studies monitoring bird communities typically rely on species classification based on bird vocalizations. Historically, this has been based on expert vo…
Bayesian Latent Class Regression with Interpretable Binary Profiles
Yuren Zhou, Yuqi Gu, David B. Dunson
High-dimensional categorical data arise in diverse scientific domains and are often accompanied by covariates. Latent class regression models are routinely used in such settings, r…
Feature aware covariance estimation, with application to mixtures of chemical exposures
Elizabeth Bersson, Kate Hoffman, Heather M. Stapleton +1
The motivation of this article is to improve inferences on the covariation in environmental exposures, motivated by data from a study of Toddlers Exposure to SVOCs in Indoor Enviro…
Learning discrete Bayesian networks with hierarchical Dirichlet shrinkage
Alexander Dombowsky, David B. Dunson
A discrete Bayesian network is a directed acyclic graph (DAG) consisting of categorical variables. Two popular approaches for DBN modeling include classification and nonparametric…