16 citations · 34 across the 11 of their papers we have counts for
5 papers · 1 filter
Latent Network Estimation and Variable Selection for Compositional Data via Variational EM
Nathan Osborne, Christine B. Peterson, Marina Vannucci
Network estimation and variable selection have been extensively studied in the statistical literature, but only recently have those two challenges been addressed simultaneously. In…
Bayesian Inference of Networks Across Multiple Sample Groups and Data Types
Elin Shaddox, Christine B. Peterson, Francesco C. Stingo +5
In this paper, we develop a graphical modeling framework for the inference of networks across multiple sample groups and data types. In medical studies, this setting arises wheneve…
Estimating the Optimal Linear Combination of Biomarkers using Spherically Constrained Optimization
Priyam Das, Debsurya De, Raju Maiti +5
In the context of a binary classification problem, the optimal linear combination of continuous predictors can be estimated by maximizing an empirical estimate of the area under th…
Bayesian Modeling of Multiple Structural Connectivity Networks During the Progression of Alzheimer's Disease
Christine B. Peterson, Nathan Osborne, Francesco C. Stingo +3
Alzheimer's disease is the most common neurodegenerative disease. The aim of this study is to infer structural changes in brain connectivity resulting from disease progression usin…
Testing hypotheses on a tree: new error rates and controlling strategies
Marina Bogomolov, Christine B. Peterson, Yoav Benjamini +1
We introduce a multiple testing procedure (TreeBH) which addresses the challenge of controlling error rates at multiple levels of resolution. Conceptually, we frame this problem as…