B. Reich

发表

Simultaneous Regression Shrinkage, Variable Selection, and Supervised Clustering of Predictors with OSCAR

H. Bondell, B. Reich, 2008, Biometrics.

Simultaneous regression shrinkage , variable selection and clustering of predictors with OSCAR

H. Bondell, B. Reich, 2006 .

False discovery control in large‐scale spatial multiple testing

Wenguang Sun, T. Cai, B. Reich, 2015, Journal of the Royal Statistical Society. Series B, Statistical methodology.

Bayesian geostatistical modelling with informative sampling locations.

D. Dunson, D. Pati, B. Reich, 2011, Biometrika.

Adding Spatially-Correlated Errors Can Mess Up the Fixed Effect You Love

J. Hodges, B. Reich, 2010 .

Multivariate Spatial-temporal Modeling and Prediction of Speciated Fine Particles

Jerry M. Davis, M. Fuentes, B. Reich, 2009, Journal of statistical theory and practice.

A spatial–temporal double-hurdle model for extremely over-dispersed avian count data

B. Reich, Earvin S. Balderama, B. Gardner, 2016 .

DeepKriging: Spatially Dependent Deep Neural Networks for Spatial Prediction

B. Reich, Yuxiao Li, Ying Sun, 2020, ArXiv.

Use of Bayesian Inference in Crystallographic Structure Refinement via Full Diffraction Profile Analysis

Alyson G. Wilson, Jacob L. Jones, Ralph C. Smith, 2016, Scientific Reports.

Use of standardized bioinformatics for the analysis of fungal DNA signatures applied to sample provenance.

Eric B. Laber, Noah Fierer, Eric B Laber, 2020, Forensic science international.

Fungi Identify the Geographic Origin of Dust Samples

Eric B. Laber, Neal S. Grantham, B. Reich, 2015, PloS one.

Identification of the variance components in the general two-variance linear model

J. Hodges, B. Reich, 2008 .

Modeling longitudinal periodontal data : A spatially-adaptive model with tools for specifying priors and checking fit

J. Hodges, B. Reich, 2007 .

Spatial Analyses of Periodontal Data Using Conditionally Autoregressive Priors Having Two Classes of Neighbor Relations

B. Carlin, J. Hodges, B. Reich, 2007 .

Effects of Residual Smoothing on the Posterior of the Fixed Effects in Disease‐Mapping Models

V. Zadnik, B. Reich, James S. Hodges, 2006, Biometrics.

Variable selection for high dimensional Bayesian density estimation: application to human exposure simulation

M. Fuentes, H. Bondell, B. Reich, 2012 .

Simultaneous Factor Selection and Collapsing Levels in ANOVA

H. Bondell, B. Reich, 2009, Biometrics.

Flexible Bayesian quantile regression for independent and clustered data.

H. Bondell, B. Reich, H. Wang, 2010, Biostatistics.

Noncrossing quantile regression curve estimation.

H. Bondell, B. Reich, H. Wang, 2010, Biometrika.

Journal of the American Statistical Association Bayesian Spatial Quantile Regression Bayesian Spatial Quantile Regression

M. Fuentes, D. Dunson, B. Reich, 2022 .

Spatiotemporal quantile regression for detecting distributional changes in environmental processes

B. Reich, 2012, Journal of the Royal Statistical Society. Series C, Applied statistics.

Bayesian Quantile Regression for Censored Data

B. Reich, Luke B. Smith, 2013, Biometrics.

Precision maps for public health

B. Reich, M. Haran, 2018, Nature.

Bayesian spatial extreme value analysis to assess the changing risk of concurrent high temperatures across large portions of European cropland

B. Shaby, B. Reich, 2012 .

A Hierarchical Model for Serially-Dependent Extremes: A Study of Heat Waves in the Western US

B. Shaby, D. Cooley, B. Reich, 2014 .

A Bayesian analysis of the effects of particulate matter using a human exposure simulator

M. Fuentes, B. Reich, J. Burke, 2006 .

Analysis of the effects of ultrafine particulate matter while accounting for human exposure

Montserrat Fuentes, Brian J Reich, M. Fuentes, 2009, Environmetrics.

Sufficient dimension reduction via bayesian mixture modeling.

Lexin Li, Brian J Reich, Howard D Bondell, 2011, Biometrics.

Sparse Bayesian Additive Nonparametric Regression with Application to Health Effects of Pesticides Mixtures

S. Ghosal, B. Reich, J. Hoppin, 2019, Statistica Sinica.

A SPATIAL CAUSAL ANALYSIS OF WILDLAND FIRE-CONTRIBUTED PM2.5 USING NUMERICAL MODEL OUTPUT.

Shu Yang, B. Reich, A. Rappold, 2020, The annals of applied statistics.

A spatial Bayesian semiparametric mixture model for positive definite matrices with applications in diffusion tensor imaging

B. Reich, D. Bandyopadhyay, Zhou Lan, 2019, Canadian Journal of Statistics.

A Spatial Markov Model for Climate Extremes

B. Shaby, B. Reich, 2018, Journal of Computational and Graphical Statistics.

A Functional Data Analysis of Spatiotemporal Trends and Variation in Fine Particulate Matter.

Jerry M. Davis, B. Reich, A. Staicu, 2018, Atmospheric environment.

A TEST FOR ISOTROPY ON A SPHERE USING SPHERICAL HARMONIC FUNCTIONS

J. Guinness, B. Reich, Indranil Sahoo, 2017, Statistica Sinica.

Optimal Seed Deployment Under Climate Change Using Spatial Models: Application to Loblolly Pine in the Southeastern US

Alfredo E Farjat, J. Guinness, B. Reich, 2017 .

Nonparametric Bayesian models for a spatial covariance.

Montserrat Fuentes, Brian J Reich, M. Fuentes, 2012, Statistical methodology.

Bayesian modeling of multivariate spatial binary data with applications to dental caries

Dipankar Bandyopadhyay, Brian J Reich, B. Reich, 2009, Statistics in medicine.

A spatial dirichlet process mixture model for clustering population genetics data.

Brian J Reich, Howard D Bondell, H. Bondell, 2011, Biometrics.

A class of covariate-dependent spatiotemporal covariance functions.

Jo Eidsvik, Michele Guindani, Brian J Reich, 2011, The annals of applied statistics.

A nonparametric Bayesian test of dependence

Brian J Reich, Howard D Bondell, Yimin Kao, 2015 .

Modeling the Effect of Temperature on Ozone-Related Mortality

B. Reich, L. Neas, A. Rappold, 2013 .

A spatial beta-binomial model for clustered count data on dental caries

B. Reich, E. Slate, D. Bandyopadhyay, 2011, Statistical methods in medical research.

A marginal cure rate proportional hazards model for spatial survival data

B. Reich, D. Bandyopadhyay, M. Nunn, 2015, Journal of the Royal Statistical Society. Series C, Applied statistics.

Distributed Inference for Spatial Extremes Modeling in High Dimensions

Emily C. Hector, B. Reich, E. Hector, 2022, Journal of the American Statistical Association.

Estimating Spatially Varying Severity Thresholds of a Forest Fire Danger Rating System Using Max-Stable Extreme-Event Modeling*

B. Shaby, A. Sullivan, B. Reich, 2015 .

A spatial capture-recapture model for territorial 4 species 5

B. Reich, B. Gardner, 2014 .

Comparing exposure metrics for the effects of fine particulate matter on emergency hospital admissions

M. Fuentes, F. Dominici, B. Reich, 2013, Journal of Exposure Science and Environmental Epidemiology.

Mean-dependent nonstationary spatial models

J. Guinness, B. Reich, A. Terando, 2019, 1905.12684.

Generalized propensity score approach to causal inference with spatial interference

Shu Yang, B. Reich, A. Rappold, 2020, Biometrics.

Comment

Eric B. Laber, B. Reich, Qian Guan, 2016, Journal of the American Statistical Association.

Soil Properties and Moisture Synergistically Influence Nontuberculous Mycobacterial Prevalence in Natural Environments of Hawai’i

B. Reich, E. Chan, A. Parsons, 2022, Applied and environmental microbiology.

Valid model-free spatial prediction

Ryan Martin, B. Reich, Huiying Mao, 2020, 2006.15640.

A spatial model for rare binary events

Samuel A. Morris, B. Reich, K. Pacifici, 2017, Environmental and Ecological Statistics.

EXTREME VALUE ANALYSIS FOR EVALUATING OZONE

B. Shaby, D. Cooley, B. Reich, 2013 .

Multilevel quantile function modeling with application to birth outcomes

M. Fuentes, B. Reich, A. Herring, 2015, Biometrics.

A semiparametric Bayesian model for spatiotemporal extremes

B. Shaby, B. Reich, A. Staicu, 2018, 1812.11699.

Uncertainty Quantification and Propagation for Projections of Extremes in Monthly Area Burned Under Climate Change

Jennifer K. Costanza, B. Reich, K. Pacifici, 2016 .

A spatial time‐to‐event approach for estimating associations between air pollution and preterm birth

Howard H. Chang, B. Reich, M. Miranda, 2013, Journal of the Royal Statistical Society. Series C, Applied statistics.

A novel statistical model for mandibular helical axis analysis.

B. Reich, I. Mizoguchi, K. Hayashi, 2009, Journal of oral rehabilitation.

Estimating Atmospheric Motion Winds from Satellite Image Data using Space-time Drift Models

J. Guinness, B. Reich, Indranil Sahoo, 2019, 1902.09653.

Accounting for Location Measurement Error in Atomic Resolution Images of Crystalline Materials

B. Reich, J. Lebeau, E. Dickey, 2019, 1910.14195.

Estimating spatially varying health effects in app-based citizen science research

Shu Yang, Brian J. Reich, Lili Wu, 2020 .

Flexible and Fast Spatial Return Level Estimation Via a Spatially Fused Penalty

Brian J. Reich, Bo Li, Danielle Sass, 2021, J. Comput. Graph. Stat..

Functional data analysis of mandibular movement using third-degree b-spline basis functions and self-modeling regression

B. Reich, Kazuo Hayashi, Seung-Pyo Lee, 2012 .

Landscape-level variation in Bt crops predict Helicoverpa zea (Lepidoptera: Noctuidae) resistance in cotton agroecosystems.

B. Reich, J. Greene, J. Bacheler, 2021, Pest management science.

Soybeans as a non-Bt refuge for Helicoverpa zea in maize-cotton agroecosystems

B. Reich, K. Hopperstad, A. Huseth, 2021, Agriculture, Ecosystems & Environment.

A spatial kernel density method to estimate the diet composition of fish

B. Reich, J. Buckel, Samantha M. Binion-Rock, 2019, Canadian Journal of Fisheries and Aquatic Sciences.

Multivariate spectral downscaling for PM2.5 species

Howard H. Chang, B. Reich, J. Mulholland, 2019, 1909.03816.

Assessment of critical exposure and outcome windows in time-to-event analysis with application to air pollution and preterm birth study.

Joshua L Warren, Howard H. Chang, Brian J Reich, 2015, Biostatistics.

Probabilistic Diffusion MRI Fiber Tracking Using a Directed Acyclic Graph Auto-Regressive Model of Positive Definite Matrices.

B. Reich, Zhou Lan, 2019, 1906.06459.

Data Mining for Extreme Behavior with Application to Ground Level Ozone

Brook T. Russell, W. C. Porter, D. Cooley, 2015 .

Urban Vegetative Cover Fragmentation in the U.S.: Associations With Physical Activity and BMI.

B. Reich, M. Floyd, M. McHale, 2016, American journal of preventive medicine.

DeepKriging: Spatially Dependent Deep Neural Networks for Spatial Prediction

B. Reich, Yuxiao Li, Ying Sun, 2020, Statistica Sinica.

Adverse neurodevelopmental eff ects and hearing loss in children associated with manganese in well water, North Carolina, USA

Barbara D. Simpson, B. Reich, A. Bateman, 2015 .

A multivariate spatial skew‐t process for joint modeling of extreme precipitation indexes

B. Reich, A. Staicu, A. Hazra, 2018, Environmetrics.

Title Optimal treatment allocations in space and time for on-line control of an emerging infectious disease Permalink

Eric B. Laber, B. Reich, K. Pacifici, 2022 .

A Feed Forward Neural Network Based on Model Output Statistics for Short-Term Hurricane Intensity Prediction

W. E. Lewis, B. Reich, L. D. Monache, 2019, Weather and Forecasting.

Dataset for: A Bayesian Mixture Model for Clustering and Selection of Feature Occurrence Rates under Mean Constraints

Marina Vannucci, Wiley Admin, Howard D. Bondell, 2017 .

Modeling Extremal Streamflow using Deep Learning Approximations and a Flexible Spatial Process

B. Shaby, B. Reich, Reetam Majumder, 2022, 2208.03344.

Selection via Penalized Credible Regions

B. Reich, A. Wilson, 2014 .

Precision maps for public health.

B. Reich, M. Haran, 2018 .

A Gaussian-process approximation to a spatial SIR process using moment closures and emulators

J. Guinness, B. Reich, Parker Trostle, 2022, 2208.03157.

Characterizing Sources of Uncertainty from Global Climate Models and Downscaling Techniques

B. Reich, F. Semazzi, R. Boyles, 2017 .

INTEGRATIVE STATISTICAL METHODS FOR EXPOSURE MIXTURES AND HEALTH.

Howard H. Chang, B. Reich, D. Fourches, 2020, The annals of applied statistics.

Matching Estimators of Causal Effects in Clustered Observational Studies with Application to Quantifying the Impact of Marine Protected Areas on Biodiversity

Shu Yang, B. Reich, D. Gill, 2022, 2210.03890.

Multiresolution Broad Area Search: Monitoring Spatial Characteristics of Gapless Remote Sensing Data

Laura J. Wendelberger, Alyson G. Wilson, B. Reich, 2022, Journal of Data Science.

SPQR: An R Package for Semi-Parametric Density and Quantile Regression

Steven G. Xu, B. Reich, Reetam Majumder, 2022, 2210.14482.

Spectral adjustment for spatial confounding.

Shu Yang, B. Reich, G. Page, 2020, Biometrika.

Time Series of Extremes

B. Shaby, B. Reich, 2015 .

Data Mining to Investigate the Meteorological Drivers for Extreme Ground Level Ozone Events

Brook T. Russell, D. Cooley, B. Reich, 2015, 1504.08080.

A Bayesian Semiparametric Method For Estimating Causal Quantile Effects

Steven G. Xu, Shu Yang, B. Reich, 2022, 2211.01591.

Pyrimethanil and chlorpyrifos air concentrations and pregnant women's urinary metabolites in the Infants' Environmental Health Study (ISA), Costa Rica.

B. Reich, J. Hoppin, C. Ruepert, 2022, Environment international.

Valid model-free spatial prediction

Ryan Martin, B. Reich, Huiying Mao, 2020, Journal of the American Statistical Association.

Block composite likelihood models for analysis of large spatial datasets

B. Shaby, B. Reich, J. Eidsvik, 2012 .

A discrete‐time survival model for porcine epidemic diarrhoea virus

B. Reich, C. Corzo, G. Machado, 2022, bioRxiv.

A Deep Learning Synthetic Likelihood Approximation of a Non-stationary Spatial Model for Extreme Streamflow Forecasting

B. Reich, Reetam Majumder, 2022, 2212.07267.

Bayesian non-parametric quantile process regression and estimation of marginal quantile effects.

Brian J Reich, Steven G Xu, Steven G. Xu, 2021, Biometrics.

Nonparametric conditional density estimation in a deep learning framework for short-term forecasting pdf

Howard D. Bondell, Brian J. Reich, David B. Huberman, 2020, Environmental and Ecological Statistics.

Circular conditional autoregressive modeling of vector fields

Danny Modlin, Brian Reich, M. Fuentes, 2012, Environmetrics.

Variable Selection in Bayesian Smoothing Spline ANOVA Models: Application to Deterministic Computer Codes

Curtis B. Storlie, Howard D. Bondell, Brian J. Reich, 2009, Technometrics.

Cretaceous climates: Mapping paleo-Köppen climatic zones using a Bayesian statistical analysis of lithologic, paleontologic, and geochemical proxies

B. Reich, L. Burgener, C. Scotese, 2023, Palaeogeography, Palaeoclimatology, Palaeoecology.

Nonparametric spatial models for extremes: application to extreme temperature data

Montserrat Fuentes, Brian Reich, M. Fuentes, 2013, Extremes.

Multisensor fusion of remotely sensed vegetation indices using space‐time dynamic linear models

B. Reich, J. Gray, Margaret Johnson, 2021, Journal of the Royal Statistical Society: Series C (Applied Statistics).

Fine-Scale Spatiotemporal Air Pollution Analysis Using Mobile Monitors on Google Street View Vehicles

Matthias Katzfuss, Margaret Johnson, Joon Jin Song, 2018, Journal of the American Statistical Association.

A Review of Spatial Causal Inference Methods for Environmental and Epidemiological Applications

Shu Yang, Brian J Reich, Yawen Guan, 2020, International statistical review = Revue internationale de statistique.

Extreme value analysis for evaluating ozone control strategies.

Kristen Foley, Daniel Cooley, Brian Reich, 2013, The annals of applied statistics.

Discussion of "Statistical Modeling of Spatial Extremes" by A. C. Davison, S. A. Padoan and M. Ribatet

B. Shaby, B. Reich, 2012, 1208.3574.

Discussion of “Statistical Modeling of Spatial Extremes”

A. Davison, S. Padoan, B. Shaby, 2012 .

A MULTIVARIATE SEMIPARAMETRIC BAYESIAN SPATIAL MODELING FRAMEWORK FOR HURRICANE SURFACE WIND FIELDS

Brian J. Reich, Montserrat Fuentes, M. Fuentes, 2007, 0709.0427.

Bridging Conditional and Marginal Inference for Spatially Referenced Binary Data

B. Reich, D. Bandyopadhyay, L. Boehm, 2013, Biometrics.

Climate change impacts on projections of excess mortality at 2030 using spatially varying ozone–temperature risk surfaces

B. Hubbell, B. Reich, A. Rappold, 2017, Journal of Exposure Science and Environmental Epidemiology.

Modeling the effect of temperature on ozone-related mortality

B. Reich, L. Neas, A. Rappold, 2013, 1412.1642.

QUANTILE REGRESSION FOR MIXED MODELS WITH AN APPLICATION TO EXAMINE BLOOD PRESSURE TRENDS IN CHINA.

Montserrat Fuentes, Brian J Reich, Penny Gordon-Larsen, 2015, The annals of applied statistics.

The R2D2 Prior for Generalized Linear Mixed Models

Howard D. Bondell, Brian J. Reich, Eric Yanchenko, 2021, 2111.10718.

R2D2 goes to space! A principled approach to setting prior distributions on spatial parameters

H. Bondell, B. Reich, Eric Yanchenko, 2023, 2301.09951.

Bayesian Regression Using a Prior on the Model Fit: The R2-D2 Shrinkage Prior

H. Bondell, B. Reich, B. Naughton, 2016, Journal of the American Statistical Association.

A Bayesian mixture model for clustering and selection of feature occurrence rates under mean constraints

Marina Vannucci, Howard D. Bondell, Brian J. Reich, 2017, Stat. Anal. Data Min..

Statistical analysis of multi‐day solar irradiance using a threshold time series model

B. Reich, Ying Sun, Carolina Euán, 2022, Environmetrics.

Multivariate spatial nonparametric modelling via kernel processes mixing.

Montserrat Fuentes, Brian Reich, M. Fuentes, 2013, Statistica Sinica.

Quantile Regression for Mixed Models

M. Fuentes, B. Reich, P. Gordon-Larsen, 2014 .

The ecology of microscopic life in household dust

Krishna Pacifici, Eric B. Laber, Noah Fierer, 2015, Proceedings of the Royal Society B: Biological Sciences.

Hierarchical Bayesian Modeling of Atomic Structural Disorder

Alyson G. Wilson, B. Reich, K. Pazdernik, 2017 .

Adverse neurodevelopmental effects and hearing loss in children associated with manganese in well water, North Carolina, USA

Barbara D. Simpson, B. Reich, R. Langley, 2015, Journal of environmental and occupational science.

The recent past and promising future for data integration methods to estimate species’ distributions

Krishna Pacifici, Brian J. Reich, David A. W. Miller, 2019, Methods in Ecology and Evolution.

A nonparametric spatial test to identify factors that shape a microbiome

Ana-Maria Staicu, Brian J. Reich, Noah Fierer, 2018, 1806.06297.

Constrained Bayesian Nonparametric Regression for Grain Boundary Energy Predictions

B. Reich, S. Patala, Haoyu Wang, 2020, 2002.00938.

Bayesian variable selection for high‐dimensional rank data

B. Reich, A. Staicu, Susheela P. Singh, 2021, Environmetrics.

A spatiotemporal recommendation engine for malaria control.

Brian J. Reich, Eric B. Laber, Qian Guan, 2020, Biostatistics.

Development of a novel statistical model for mandibular kinematics.

B. Reich, Kazuo Hayashi, Seung-Pyo Lee, 2010, Medical engineering & physics.

Kryging: geostatistical analysis of large-scale datasets using Krylov subspace methods

A. Saibaba, B. Reich, Yawen Guan, 2020, Statistics and Computing.

Global forensic geolocation with deep neural networks pdf

Matthew J. Gebert, Krishna Pacifici, Brian J. Reich, 2019, Journal of the Royal Statistical Society: Series C (Applied Statistics).

The links between agriculture, Anopheles mosquitoes, and malaria risk in children younger than 5 years in the Democratic Republic of the Congo: a population-based, cross-sectional, spatial study

B. Reich, S. Meshnick, M. Emch, 2018, The Lancet. Planetary health.

Bayesian Nonparametric Policy Search With Application to Periodontal Recall Intervals

Dipankar Bandyopadhyay, Brian J. Reich, Eric B. Laber, 2018, Journal of the American Statistical Association.

Optimal treatment allocations in space and time for on‐line control of an emerging infectious disease

John M Drake, Krishna Pacifici, Eric B. Laber, 2018, Journal of the Royal Statistical Society. Series C, Applied statistics.

Confounder selection via penalized credible regions

Brian J Reich, Ander Wilson, B. Reich, 2014, Biometrics.

Estimation and Prediction in Spatial Models With Block Composite Likelihoods

Jo Eidsvik, Brian J. Reich, Jarad Niemi, 2014 .

Malware Detection Using Nonparametric Bayesian Clustering and Classification Techniques

Curtis B. Storlie, Brian J. Reich, Blake Anderson, 2015, Technometrics.

Consistent High-Dimensional Bayesian Variable Selection via Penalized Credible Regions

Brian J Reich, Howard D Bondell, H. Bondell, 2012, Journal of the American Statistical Association.

Resolving misaligned spatial data with integrated species distribution models

Krishna Pacifici, Brian J Reich, David A W Miller, 2019, Ecology.

Integrating multiple data sources in species distribution modeling: a framework for data fusion.

Krishna Pacifici, Brian J Reich, David A W Miller, 2017, Ecology.

Deep Distribution Regression pdf

Rui Li, Howard D. Bondell, Brian J. Reich, 2019, Comput. Stat. Data Anal..

Surface Estimation, Variable Selection, and the Nonparametric Oracle Property.

Brian J Reich, Howard D Bondell, Curtis B Storlie, 2011, Statistica Sinica.

A Locally Adaptive Penalty for Estimation of Functions With Varying Roughness

Curtis B. Storlie, Howard D. Bondell, Brian J. Reich, 2010 .

A spatial capture‐recapture model for territorial species

Brian J. Reich, Beth Gardner, B. Reich, 2014, 1405.1976.

Fully Bayesian spectral methods for imaging data

Russell T. Shinohara, Ana-Maria Staicu, Brian J. Reich, 2018, Biometrics.

Scalar‐on‐image regression via the soft‐thresholded Gaussian process

B. Reich, A. Staicu, Jian Kang, 2016, Biometrika.

Using spatial cross-correlation image analysis to characterize the influence of strain rate on plastic damage in molecular dynamics simulations

B. Reich, D. Brenner, D. Li, 2017 .

Statistical and image analysis for characterizing simulated atomic-scale damage in crystals

B. Reich, D. Brenner, D. Li, 2017 .

Accounting for Location Measurement Error in Imaging Data With Application to Atomic Resolution Images of Crystalline Materials

B. Reich, J. Lebeau, E. Dickey, 2019, Technometrics.

Spatial–temporal mesoscale modeling of rainfall intensity using gage and radar data

Montserrat Fuentes, Gyuwon Lee, Brian Reich, 2008, 0901.3478.

A penalized complexity prior for deep Bayesian transfer learning with application to materials informatics

B. Reich, Jonathan P. Williams, M. Abba, 2022, 2201.12401.

Spatial-temporal association between fine particulate matter and daily mortality

Brian J. Reich, Montserrat Fuentes, Jungsoon Choi, 2009, Comput. Stat. Data Anal..

Time-to-event analysis of fine particle air pollution and preterm birth: results from North Carolina, 2001-2005.

Brian J. Reich, Marie Lynn Miranda, Howard H. Chang, 2012, American journal of epidemiology.

A Multivariate Dynamic Spatial Factor Model for Speciated Pollutants and Adverse Birth Outcomes

Maria A. Terres, M. Fuentes, G. Shaw, 2017, International journal of environmental research and public health.

Geostatistical modeling of positive‐definite matrices: An application to diffusion tensor imaging

Dipankar Bandyopadhyay, Joseph Guinness, Brian J Reich, 2019, Biometrics.

Modeling climate change effects on the height growth of loblolly pine.

Alfredo E Farjat, B. Reich, R. Whetten, 2015 .

Spatial variable selection methods for investigating acute health effects of fine particulate matter components

Montserrat Fuentes, Francesca Dominici, Brian J Reich, 2015, Biometrics.

A LATENT FACTOR MODEL FOR SPATIAL DATA WITH INFORMATIVE MISSINGNESS.

Dipankar Bandyopadhyay, Brian J Reich, B. Reich, 2010, The annals of applied statistics.

Chang et al. Respond to “Environmental Exposures and Preterm Birth”

Howard H. Chang, B. Reich, M. Miranda, 2012 .

Response to Invited Commentary Chang et al . Respond to ‘ ‘ Environmental Exposures and Preterm Birth ’ ’

Howard H. Chang, B. Reich, M. Miranda, 2011 .

Impacts of fire smoke plumes on regional air quality, 2006–2013

B. Reich, A. Rappold, M. Ruminski, 2018, Journal of Exposure Science & Environmental Epidemiology.

A spectral method for spatial downscaling

Howard H. Chang, Brian J Reich, Howard H Chang, 2014, Biometrics.

MIMIX: A Bayesian Mixed-Effects Model for Microbiome Data From Designed Experiments

Brian J. Reich, Kevin Gross, Elizabeth T. Borer, 2017, Journal of the American Statistical Association.

Occupancy estimation for rare species using a spatially‐adaptive sampling design

Krishna Pacifici, Michael J. Conroy, Brian J. Reich, 2016 .

Relationships between urban green land cover and human health at different spatial resolutions

B. Reich, M. Floyd, M. McHale, 2018, Urban Ecosystems.

A deep learning synthetic likelihood approximation of a non-stationary spatial model for extreme streamflow forecasting

B. Reich, Reetam Majumder, 2022, Spatial Statistics.

High Dimensional Linear Regression via the R2-D2 Shrinkage Prior

Howard D. Bondell, Brian J. Reich, Yan Zhang, 2016, 1609.00046.

Hierarchical dose–response modeling for high‐throughput toxicity screening of environmental chemicals

David M. Reif, David M Reif, Brian J Reich, 2014, Biometrics.

Long-term, medium spatial resolution annual land surface phenology with a Bayesian hierarchical model

B. Reich, J. Gray, Xiaojie Gao, 2021 .

A deep learning approach to identify smoke plumes in satellite imagery in near real-time for health risk communication

Brian J. Reich, Ana G. Rappold, Martin Cope, 2020, Journal of Exposure Science & Environmental Epidemiology.

A comparison of statistical and machine learning methods for creating national daily maps of ambient PM2.5 concentration.

James A. Mulholland, Veronica J. Berrocal, Howard H. Chang, 2019, Atmospheric environment.

Analysis of computationally demanding models with continuous and categorical inputs

Jon C. Helton, Cédric J. Sallaberry, Curtis B. Storlie, 2013, Reliab. Eng. Syst. Saf..

A Bayesian semi-parametric mixture model for bivariate extreme value analysis with application to precipitation forecasting

Yuan Tian, Brian J. Reich, B. Reich, 2021 .

Exploration and Inference in Spatial Extremes Using Empirical Basis Functions

Samuel A. Morris, B. Reich, E. Thibaud, 2019, Journal of Agricultural, Biological and Environmental Statistics.

Exploration and Inference in Spatial Extremes Using Empirical Basis Functions

Brian J. Reich, Emeric Thibaud, Samuel A. Morris, 2018, Journal of Agricultural, Biological and Environmental Statistics.

A Spatio-Temporal Model for Longitudinal Image-on-Image Regression

Russell T. Shinohara, Ana-Maria Staicu, Daniel S. Reich, 2019, Statistics in biosciences.

A semiparametric spatiotemporal Bayesian model for the bulk and extremes of the Fosberg Fire Weather Index

B. Shaby, B. Reich, A. Staicu, 2018 .

Integrating auxiliary data in optimal spatial design for species distribution modelling

Krishna Pacifici, Brian J. Reich, Jonathan Stallings, 2018 .

Social inequalities in residential exposure to road traffic noise: An environmental justice analysis based on the RECORD Cohort Study

Basile Chaix, Brian J Reich, Sabrina Havard, 2011, Occupational and Environmental Medicine.

A space‐time skew‐t model for threshold exceedances

Daniel Cooley, Brian J Reich, Samuel A Morris, 2017, Biometrics.

A HIERARCHICAL MAX-STABLE SPATIAL MODEL FOR EXTREME PRECIPITATION.

Brian J Reich, B. Shaby, B. Reich, 2013, The annals of applied statistics.

Avian response to shade‐layer restoration in coffee plantations in Puerto Rico

B. Reich, K. Pacifici, Kathryn E. Battle, 2018 .

Transitioning Machine Learning from Theory to Practice in Natural Resources Management

Brian J. Reich, Khara Grieger, Sheila M. Saia, 2020, Ecological Modelling.

Spatiotemporal signal detection using continuous shrinkage priors

Dipankar Bandyopadhyay, Brian J Reich, An-Ting Jhuang, 2020, Statistics in medicine.

A Bayesian approach to probabilistic streamflow forecasts

Hui Wang, Brian J. Reich, Yeo Howe Lim, 2013 .

Relationships between urban green land cover and human health at different spatial resolutions

B. Reich, M. Floyd, M. McHale, 2018, Urban Ecosystems.

Occupancy and Abundance of Eleutherodactylus Frogs in Coffee Plantations in Puerto Rico

B. Reich, K. Pacifici, A. Terando, 2017, Herpetologica.

The R2D2 Prior for Generalized Linear Mixed Models

H. Bondell, B. Reich, Eric Yanchenko, 2021, 2111.10718.

Spatio-temporal DeepKriging for Interpolation and Probabilistic Forecasting

Ying Sun, B. Reich, Pratik Nag, 2023, Spatial Statistics.

Basics of Bayesian inference

Bradley P. Carlin, Scott M. Berry, Peter Müller, 2019, Bayesian Statistical Methods.

Nonparametric Bayesian models for a spatial covariance 1

M. Fuentes, B. Reich, 2011 .

Estimating the drivers of species distributions with opportunistic data using mediation analysis

Krishna Pacifici, Brian J. Reich, David B. Huberman, 2020, Ecosphere.

Monitoring Deforestation Using Multivariate Bayesian Online Changepoint Detection with Outliers

Brian J. Reich, Josh M. Gray, Laura J. Wendelberger, 2021, 2112.12899.

Bayesian Statistical Methods

Brian J. Reich, Sujit K. Ghosh, S. Ghosh, 2019 .

Nonparametric spatial models for extremes: application to extreme temperature data

M. Fuentes, B. Reich, J. Henry, 2012, Extremes.

A Spatial Analysis of Basketball Shot Chart Data

Bradley P. Carlin, James S. Hodges, Brian J. Reich, 2006 .

Bivariate DeepKriging for Large-scale Spatial Interpolation of Wind Fields

Ying Sun, B. Reich, Pratik Nag, 2023, 2307.08038.

A finite-dimensional construction of a max-stable process for spatial extremes

Brian J. Reich, Benjamin A. Shaby, B. Shaby, 2011 .

Spatial prediction of crystalline defects observed in molecular dynamic simulations of plastic damage

Donald W. Brenner, Brian J. Reich, Geoffrey Colin Lee Peterson, 2017 .

How predictable is plastic damage at the atomic scale

Donald W. Brenner, Brian J. Reich, Geoffrey Colin Lee Peterson, 2017 .

A Multiresolution Approach to Estimating the Value Added by Regional Climate Models

Stephan R. Sain, Brian J. Reich, Ryan J. Parker, 2015 .

Bayesian analysis of a reduced-form air quality model.

Brian J Reich, Sergey L Napelenok, Kristen M Foley, 2012, Environmental science & technology.

A Fused Lasso Approach to Nonstationary Spatial Covariance Estimation

Jo Eidsvik, Brian J. Reich, Ryan J. Parker, 2016 .

A Fused Lasso Approach to Nonstationary Spatial Covariance Estimation

B. Reich, J. Eidsvik, R. J. Parker, 2016, Journal of Agricultural, Biological, and Environmental Statistics.

Spatial Signal Detection Using Continuous Shrinkage Priors

Brian J. Reich, Jacob L. Jones, An-Ting Jhuang, 2019, Technometrics.

A Temperature Monitoring Infrastructure and Process for Improving Data Center Energy Efficiency with Results for a High Performance Computing Data Center

Curtis B. Storlie, Sarah E. Michalak, Brian J. Reich, 2018, Analytic Methods in Systems and Software Testing.

Bayesian Approaches to Uncertainty Quantification and Structure Refinement from X-Ray Diffraction

Alyson G. Wilson, Brian J. Reich, Jacob L. Jones, 2018 .

Modeling Longitudinal Spatial Periodontal Data: A Spatially Adaptive Model with Tools for Specifying Priors and Checking Fit

James S Hodges, Brian J Reich, J. Hodges, 2008, Biometrics.

A Markov-switching model for heat waves

B. Shaby, D. Cooley, B. Reich, 2014, 1405.3904.

Sequential Optimization in Locally Important Dimensions

Brian J. Reich, Munir A. Winkel, Jonathan W. Stallings, 2018, Technometrics.

Nearest-Neighbor Neural Networks for Geostatistics

Haoyu Wang, Brian J. Reich, Yawen Guan, 2019, 2019 International Conference on Data Mining Workshops (ICDMW).

Statistica Sinica Preprint

Ying Sun, B. Reich, Yuxiao Li, 2022 .

Modeling Multivariate Mixed-Response Functional Data

Ana-Maria Staicu, Brian J. Reich, Beth A. Tidemann-Miller, 2016, 1601.02461.

Statistical Downscaling with Spatial Misalignment: Application to Wildland Fire $$\hbox {PM}_{2.5}$$ PM 2.5 Concentration Forecasting

Brian J. Reich, Yawen Guan, Ana G. Rappold, 2019, Journal of agricultural, biological, and environmental statistics.

Spatiotemporal Modeling of Node Temperatures in Supercomputers

Brian J Reich, Curtis B Storlie, William N Rust, 2015, 1505.06275.

Bayesian Quantile Regression for Censored Data

B. Reich, Luke B. Smith, 2013, Biometrics.

Spatial Shrinkage Via the Product Independent Gaussian Process Prior

J. Guinness, B. Reich, R. Shinohara, 2018, J. Comput. Graph. Stat..

A Spatio-Temporal Model for Longitudinal Image-on-Image Regression

D. Reich, B. Reich, R. Shinohara, 2017, Statistics in Biosciences.

Evaluating temporally weighted kernel density methods for predicting the next event location in a series

Brian J. Reich, Michael D. Porter, B. Reich, 2012, Ann. GIS.

Modeling extremal streamflow using deep learning approximations and a flexible spatial process

B. Shaby, B. Reich, Reetam Majumder, 2022, The Annals of Applied Statistics.

Partially supervised spatiotemporal clustering for burglary crime series identification

Brian J. Reich, Michael D. Porter, B. Reich, 2015 .

A Nonparametric Spatial Model for Periodontal Data With Nonrandom Missingness

Dipankar Bandyopadhyay, Brian J Reich, Howard D Bondell, 2013, Journal of the American Statistical Association.

Multivariate spatial prediction of air pollutant concentrations with INLA

Howard H. Chang, B. Reich, Wenlong Gong, 2021, Environmental research communications.

A Spatial Dirichlet Process Mixture Model for Clustering Population Genetics Data

H. Bondell, B. Reich, 2011, Biometrics.

Comment on Article by Page and Quintana

M. Fuentes, B. Reich, 2016 .

A Bayesian multivariate functional model with spatially varying coefficient approach for modeling hurricane track data

Brian J. Reich, Montserrat Fuentes, Hossein Moradi Rekabdarkolaee, 2019, Spatial Statistics.

A Bayesian semi-parametric hybrid model for spatial extremes with unknown dependence structure

B. Reich, Yuan Tian, 2020, 2003.10592.

Bayesian Variable Selection for Multivariate Spatially Varying Coefficient Regression

M. Fuentes, B. Reich, A. Herring, 2010, Biometrics.

Multiple window discrete scan statistic for higher-order Markovian sequences

Donald E. K. Martin, Brian J. Reich, D. A. Coleman, 2015 .

Retracted: Multi‐model penalized regression

Alyson G. Wilson, Laura J. Wendelberger, B. Reich, 2020, Stat. Anal. Data Min..

Beyond Simple Trend Tests: Detecting Significant Changes in Design‐Flood Quantiles

B. Reich, S. Archfield, A. Sankarasubramanian, 2023, Geophysical Research Letters.