Brian Reich

Bio

Brian uses geospatial analytics to explore patterns in data from the environmental, physical and materials sciences. He develops approaches using spatial statistics, extreme value analysis, quantile regression, variable selection and dimension reduction. His interests include both methodological questions in statistics and applications of statistical methods to problems such as air pollution and climate change.

Publications

• A nonparametric test of group distributional differences for hierarchically clustered functional data , BIOMETRICS (2023)
• Distributed Inference for Spatial Extremes Modeling in High Dimensions , JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2023)
• A SPATIAL CAUSAL ANALYSIS OF WILDLAND FIRE-CONTRIBUTED PM2.5 USING NUMERICAL MODEL OUTPUT , ANNALS OF APPLIED STATISTICS (2022)
• A discrete-time survival model for porcine epidemic diarrhoea virus , TRANSBOUNDARY AND EMERGING DISEASES (2022)
• Bayesian Regression Using a Prior on the Model Fit: The R2-D2 Shrinkage Prior , JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2022)
• Bayesian spatial modeling using random Fourier frequencies , SPATIAL STATISTICS (2022)
• Discussion on "Spatial plus : A novel approach to spatial confounding" by Dupont, Wood, and Augustin , BIOMETRICS (2022)
• Estimating intervention effects on infectious disease control: The effect of community mobility reduction on Coronavirus spread , SPATIAL STATISTICS (2022)
• Exposure to common-use pesticides, manganese, lead, and thyroid function among pregnant women from the Infants' Environmental Health (ISA) study, Costa Rica , SCIENCE OF THE TOTAL ENVIRONMENT (2022)
• Generalized propensity score approach to causal inference with spatial interference , BIOMETRICS (2022)