13 citations · 39 across the 28 of their papers we have counts for
10 papers · 1 filter
Model-based indicators for co-clustered environments and species communities
Braden Scherting, Otso Ovaskainen, Tomas Roslin +1
Accurate biodiversity monitoring is essential for effective environmental policy, yet current practices often rely on arbitrarily defined ecosystems, communities, and ad-hoc indica…
Uncertainty Quantification in Bayesian Clustering
Garritt L. Page, Andrés F. Barrientos, David B. Dahl +1
Bayesian clustering methods have the widely touted advantage of providing a probabilistic characterization of uncertainty in clustering through the posterior distribution. An amazi…
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…
Inference on covariance structure in high-dimensional multi-view data
Lorenzo Mauri, David B. Dunson
This article focuses on covariance estimation for multi-view data. Popular approaches rely on factor-analytic decompositions that have shared and view-specific latent factors. Post…
A note on simulation methods for the Dirichlet-Laplace prior
Luis Gruber, Gregor Kastner, Anirban Bhattacharya +3
Bhattacharya et al. (2015, Journal of the American Statistical Association 110(512): 1479-1490) introduce a novel prior, the Dirichlet-Laplace (DL) prior, and propose a Markov chai…
Targeted empirical Bayes for more supervised joint factor analysis
Glenn Palmer, David B. Dunson
Joint Bayesian factor models are popular for characterizing relationships between multivariate correlated predictors and a response variable. Standard models assume that all variab…
Scalable and robust regression models for continuous proportional data
Changwoo J. Lee, Benjamin K. Dahl, Otso Ovaskainen +1
Beta regression is used routinely for continuous proportional data, but it often encounters practical issues such as a lack of robustness to misspecification of the beta distributi…
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…
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…
Quantifying sleep apnea heterogeneity using hierarchical Bayesian modeling
Glenn Palmer, Narat Srivali, David B. Dunson
Obstructive Sleep Apnea (OSA) is a breathing disorder during sleep that affects millions of people worldwide. The diagnosis of OSA often occurs through an overnight polysomnogram (…