output
20052025
most citedMulti-system Bayesian constraints on the transport coefficients of QCD matter

308 citations

Showing stat.APShow all

7 papers · 1 filter

stat.AP2018

Computer model calibration based on image warping metrics: an application for sea ice deformation

Yawen Guan, Christian Sampson, J. Derek Tucker +4

Arctic sea ice plays an important role in the global climate. Sea ice models governed by physical equations have been used to simulate the state of the ice including characteristic…

stat.AP2018★ 22 cited

Fine-scale spatiotemporal air pollution analysis using mobile monitors on Google Street View vehicles

Yawen Guan, Margaret Johnson, Matthias Katzfuss +4

People are increasingly concerned with understanding their personal environment, including possible exposure to harmful air pollutants. In order to make informed decisions on their…

stat.AP2018

Hierarchical infinite factor model for improving the prediction of surgical complications for geriatric patients

Elizabeth Lorenzi, Ricardo Henao, Katherine Heller

We develop a hierarchical infinite latent factor model (HIFM) to appropriately account for the covariance structure across subpopulations in data. We propose a novel Hierarchical D…

stat.AP2015★ 2 cited

Bayesian Models for Heterogeneous Personalized Health Data

Kai Fan, Allison E. Aiello, Katherine A. Heller

The purpose of this study is to leverage modern technology (such as mobile or web apps in Beckman et al. (2014)) to enrich epidemiology data and infer the transmission of disease.…

stat.AP2012★ 36 cited

Multiple imputation for sharing precise geographies in public use data

Hao Wang, Jerome P. Reiter

When releasing data to the public, data stewards are ethically and often legally obligated to protect the confidentiality of data subjects' identities and sensitive attributes. The…

stat.AP2010★ 7 cited

An integrative analysis of cancer gene expression studies using Bayesian latent factor modeling

Daniel Merl, Julia Ling-Yu Chen, Jen-Tsan Chi +1

We present an applied study in cancer genomics for integrating data and inferences from laboratory experiments on cancer cell lines with observational data obtained from human brea…