E. George

发表

A g-prior extension for p>n

Yuzo Maruyama, E. George, 2008 .

Bayesian CART Model Search

H. Chipman, E. George, R. McCulloch, 1998 .

Journal of the American Statistical Association is currently published by American Statistical Association.

E. George, R. McCulloch, Edward I. George, 2007 .

The risk inflation criterion for multiple regression

Dean P. Foster, Dean Phillips Foster, E. George, 1994 .

Bayesian Additive Regression Trees

H. Chipman, E. George, R. McCulloch, 2006 .

The Variable Selection Problem

E. George, 2000 .

BART: Bayesian Additive Regression Trees

H. Chipman, E. George, R. McCulloch, 2008, 0806.3286.

Explaining the Gibbs Sampler

G. Casella, E. George, 1992 .

Covariance Adjustments for the Analysis of Randomized Field Experiments

A. Buja, L. Brown, E. George, 2013, Evaluation review.

Improved Precision in Estimating Average Treatment Effects

A. Buja, E. George, R. Berk, 2013, 1311.0291.

Shrinkage Estimation of Price and Promotional Elasticities: Seemingly Unrelated Equations

Robert C. Blattberg, E. George, R. Blattberg, 1991 .

Calibration and empirical Bayes variable selection

Dean P. Foster, E. George, 2000 .

APPROACHES FOR BAYESIAN VARIABLE SELECTION

E. George, R. McCulloch, 1997 .

Flexible empirical Bayes estimation for wavelets

M. Clyde, E. George, 2000 .

Combining Minimax Shrinkage Estimators

E. George, 1986 .

A formal bayes multiple shrinkage estimator

E. George, 1986 .

Minimax Multiple Shrinkage Estimation

E. George, 1986 .

MULTIPLE SHRINKAGE GENERALIZATIONS OF THE JAMES-STEIN ESTIMATOR

E. George, 1987 .

Sampling random polygons

E. George, 1987, Journal of Applied Probability.

Capture—recapture estimation via Gibbs sampling

E. George, 1992 .

Bayesian Treed Generalized Linear Models

H. Chipman, E. George, R. McCulloch, 2003 .

Maximally informative statistics

D. R. Wolf, E. George, 2000, physics/0010039.

Conjugate likelihood distributions

A. F. Smith, E. George, U. Makov, 1993 .

Empirical Bayes Methods for Combining Likelihoods: Comment

B. Efron, C. Morris, A. Gelfand, 1996 .

Bayesian Ensemble Learning

Edward I. George, Robert E. McCulloch, Hugh A. Chipman, 2006, NIPS.

Ensemble of trees approaches to risk adjustment for evaluating a hospital’s performance

Dylan S. Small, E. George, M. Traskin, 2015, Health care management science.

Redefine statistical significance

Christopher D. Chambers, Felix D. Schönbrodt, Jeffrey N. Rouder, 2017, Nature Human Behaviour.

Bayes and big data: the consensus Monte Carlo algorithm

Edward I. George, Robert E. McCulloch, Hugh A. Chipman, 2016, Big Data and Information Theory.

Determinantal Priors for Variable Selection

E. George, V. Rocková, 2014 .

Making sense of a forest of treesH

E. George, A. Chipman, E. R., 2007 .

Ozone Exposure and Population Density in Harris County, Texas

Rong Chen, R. Carroll, E. George, 1997 .

Fast Bayesian Factor Analysis via Automatic Rotations to Sparsity

E. George, V. Rocková, V. Ročková, 2016 .

The Median Probability Model and Correlated Variables

James O. Berger, Veronika Rockova, Edward I. George, 2018, Bayesian Analysis.

Bayesian stochastic search for VAR model restrictions

Dongchu Sun, E. George, Shawn Ni, 2008 .

Negotiating multicollinearity with spike-and-slab priors

E. George, V. Rocková, V. Ročková, 2014, Metron.

Exponential and bayesian conjugate families: Review and extensions

C. Morris, J. Bernardo, A. F. Smith, 1997 .

Fully Bayes factors with a generalized g-prior

Yuzo Maruyama, E. George, 2008, 0801.4410.

Model Uncertainty

M. Clyde, E. George, 2003 .

Valid Post-selection Inference in Assumption-lean Linear Regression

Arun K. Kuchibhotla, A. Buja, L. Brown, 2018, 1806.04119.

Models as Approximations, Part I: A Conspiracy of Nonlinearity and Random Regressors in Linear Regression

A. Buja, L. Brown, E. George, 2014, 1404.1578.

A Model Free Perspective for Linear Regression: Uniform-in-model Bounds for Post Selection Inference

Arun K. Kuchibhotla, A. Buja, L. Brown, 2018 .

Valid post-selection inference in model-free linear regression

Arun K. Kuchibhotla, A. Buja, L. Brown, 2020 .

Assumption Lean Regression

Weijie J. Su, Arun K. Kuchibhotla, A. Buja, 2018, The American Statistician.

The Spike-and-Slab LASSO

E. George, V. Rocková, V. Ročková, 2018 .

A Tribute to Charles Stein

E. George, W. Strawderman, 2012, 1203.4664.

Bayesian Model Selection

Edward I. George, E. George, 2006 .

A bayesian model for collaborative filtering

Edward I. George, Yung-Hsin Chien, E. George, 1999, AISTATS.

Models as Approximations - A Conspiracy of Random Regressors and Model Deviations Against Classical Inference in Regression

Andreas Buja, Richard A. Berk, Edward I. George, 2015 .

Hospital Mortality Rate Estimation for Public Reporting

P. Rosenbaum, E. George, V. Satopää, 2015 .

Mortality Rate Estimation and Standardization for Public Reporting: Medicare’s Hospital Compare

E. I. George, J. H. Silber, P. R. Rosenbaum, 2015, 1510.00842.

Capture-Recapture Models and Bayesian Sampling

C. Robert, E. George, 1990 .

Posterior Odds with a Generalized Hyper-g-Prior

Yuzo Maruyama, E. George, 2014 .

Optimal pricing using online auction experiments: A Pólya tree approach

Sam K. Hui, E. George, 2012, 1203.3653.

Model-based analysis of concept maps

Sam K. Hui, E. George, Yanliu Huang, 2008 .

Admissible Predictive Density Estimation 1

L. Brown, E. George, Xu Xinyi, 2008 .

Empirical Bayes vs. Fully Bayes Variable Selection

Edward I. George, Wen Cui, E. George, 2008 .

Improved minimax predictive densities under Kullback-Leibler loss

Feng Liang, Edward I. George, Xinyi Xu, 2006 .

Estimation up to a Change-Point

Dean P. Foster, Edward I. George, Dean Phillips Foster, 1993 .

Estimation under Profit-Driven Loss Functions

Edward I. George, Robert C. Blattberg, E. George, 1992 .

Bayesian Spatial Clustering of Crime in Philadelphia with Particle Optimization

Sameer K. Deshpande, Shane T. Jensen, E. George, 2019 .

Variance Prior Forms for High-Dimensional Bayesian Variable Selection

Gemma E. Moran, E. George, V. Rocková, 2018, Bayesian Analysis.

New and Evolving Roles of Shrinkage in Large-Scale Prediction and Inference

E. George, Gourab Mukherjee, É. Marchand, 2019 .

From Minimax Shrinkage Estimation to Minimax Shrinkage Prediction

Feng Liang, Edward I. George, Xinyi Xu, 2012, 1203.5617.

Bayesian Predictive Density Estimation

E. George, Xinyi Xu, 2010 .

Models as Approximations — A Conspiracy of Random Regressors and Model Misspecification Against Classical Inference in Regression

A. Buja, L. Brown, E. George, 2016 .

On variance estimation for Bayesian variable selection

Gemma E. Moran, E. George, V. Rocková, 2018 .

Working with Misspecified Regression Models

A. Buja, L. Brown, E. George, 2018 .

Statistica Sinica Preprint No : SS-2016-0546 R 1 Title Calibrated Percentile Double Bootstrap For Robust Linear Regression Inference

A. Buja, L. Brown, E. George, 2017 .

PREDICTIVE DENSITY ESTIMATION FOR MULTIPLE REGRESSION

E. George, Xinyi Xu, 2008, Econometric Theory.

University of Pennsylvania Department of Statistics

D. F. Morrison, E. George, A. Krieger, 2012 .

A Latent Variable Perspective of Copula Modeling

Shane T. Jensen, E. George, 2011 .

Uncovering Patterns for Adverse Pregnancy Outcomes with Spatial Analysis: Evidence from Philadelphia

Silvia P. Canel'on, E. George, M. Boland, 2021, 2105.04981.

Crime in Philadelphia: Bayesian Clustering with Particle Optimization

Sameer K. Deshpande, Shane T. Jensen, E. George, 2019, Journal of the American Statistical Association.

Ensemble minimaxity of James-Stein estimators

L. Brown, Yuzo Maruyama, E. George, 2022, 2206.10856.

1 Our Approach : Spike-and-Slab Lasso Biclustering

Gemma E. Moran, E. George, V. Rocková, 2019 .

Adaptive Direction Sampling

Walter R. Gilks, Gareth O. Roberts, Edward I. George, 1994 .

Edinburgh Research Explorer Redefine statistical significance

Felix D. Schönbrodt, Jeffrey N. Rouder, T. Cook, 2019 .

Bayesian POst model Selection Inference

Edward George, Daniel Yekutieli, D. Yekutieli, 2012 .

Clustering Areal Units at Multiple Levels of Resolution to Model Crime in Philadelphia

Shane T. Jensen, E. George, Cecilia Balocchi, 2021, 2112.02059.

Statistical inference and Monte Carlo algorithms

Jun S. Liu, Xiao-Li Meng, L. Wasserman, 1996 .

Improving Medicare's Hospital Compare Mortality Model.

P. Rosenbaum, E. George, V. Satopää, 2016, Health services research.

Bayesian Model Selection

E. George, 2006 .

Maximally informative statistics

D. R. Wolf, E. George, 2000, physics/0010039.

UNIFORM-IN-SUBMODEL BOUNDS FOR LINEAR REGRESSION IN A MODEL-FREE FRAMEWORK

Arun K. Kuchibhotla, A. Buja, L. Brown, 2018, Econometric Theory.

Ensemble minimaxity of James‐Stein estimators

L. Brown, Yuzo Maruyama, E. George, 2022, Stat.

Improved minimax predictive densities under Kullback-Leibler loss

Feng Liang, E. George, Xinyi Xu, 2006, math/0605432.

A Latent Variable Perspective of Copula Modeling

Shane T. Jensen, E. George, 2011 .

Working with Misspecified Regression Models

A. Buja, E. George, R. Berk, 2017, Journal of Quantitative Criminology.

Meta-analyses using information reweighting: An application to online advertising

Eric T. Bradlow, E. George, Pengyuan Wang, 2014, Quantitative Marketing and Economics.

UNIFORM-IN-SUBMODEL BOUNDS FOR LINEAR REGRESSION IN A MODEL-FREE FRAMEWORK

Andreas Buja, Arun Kumar Kuchibhotla, Edward I. George, 2018, Econometric Theory.

POSTERIOR PROPRIETY IN SOME HIERARCHICAL EXPONENTIAL FAMILY MODELS

E. George, Zuoshun Zhang, 2000 .

Clustering Areal Units at Multiple Levels of Resolution to Model Crime Incidence in Philadelphia

Edward I. George, Cecilia Balocchi, Shane T. Jensen, 2021, 2112.02059.

Influential Observations in Bayesian Regression Tree Models

E. George, R. McCulloch, M. Pratola, 2022, 2203.14102.

Models as Approximations I: Consequences Illustrated with Linear Regression

Kai Zhang, Andreas Buja, Mikhail Traskin, 2014, Statistical Science.

Heteroscedastic BART via Multiplicative Regression Trees

M. T. Pratola, H. A. Chipman, E. I. George, 2020 .

Variable selection for BART: An application to gene regulation

Edward I. George, Shane T. Jensen, Adam Kapelner, 2013, 1310.4887.

The Practical Implementation of Bayesian Model Selection

Edward I. George, Robert E. McCulloch, Hugh A. Chipman, 2001 .

Empirical Bayes Estimation in Wavelet Nonparametric Regression

Edward I. George, Merlise A. Clyde, M. Clyde, 1999 .

On obtaining invariant prior distributions

E. George, R. McCulloch, 1993 .

Bayesian prediction with adaptive ridge estimators

Edward I. George, David G.T. Denison, D. Denison, 2012 .

Bayesian models in business and industry

Edward I. George, Fabrizio Ruggeri, E. George, 2006 .

Perspectives on Bayesian Methods and Big Data

Eric T. Bradlow, Greg M. Allenby, Edward I. George, 2014, Customer Needs and Solutions.

A Bayesian Hierarchical Modeling Framework for Geospatial Analysis of Adverse Pregnancy Outcomes

Edward I. George, Ray Bai, Mary R. Boland, 2021 .

Calibration and empirical Bayes variable selection

Dean Phillips Foster, E. George, 2000 .

Bayesian flexible modeling of trip durations

Edward I. George, Robert E. McCulloch, Hugh A. Chipman, 2010 .

Misspecified Mean Function Regression

Andreas Buja, Kai Zhang, Linda Zhao, 2014 .

Bayesian Treed Models

Edward I. George, Robert E. McCulloch, Hugh A. Chipman, 2002, Machine Learning.

Managing Multiple Models

Edward I. George, Robert E. McCulloch, Hugh A. Chipman, 2001, AISTATS.

Spike-and-Slab Meets LASSO: A Review of the Spike-and-Slab LASSO

E. George, V. Rocková, Ray Bai, 2020, Handbook of Bayesian Variable Selection.

Comment: Regularization via Bayesian Penalty Mixing

Edward I. George, Veronika Ročková, E. George, 2020, Technometrics.

Bayesian Forecasting of Prepayment Rates for Individual Pools of Mortgages

Edward I. George, Elmira Popova, Ivillina Popova, 2008 .

Uniform Correlation Mixture of Bivariate Normal Distributions and Hypercubically Contoured Densities That Are Marginally Normal

Lawrence D. Brown, Linda Zhao, Kai Zhang, 2014, 1511.06190.

Models as Approximations II: A Model-Free Theory of Parametric Regression

Andreas Buja, Linda Zhao, Arun K. Kuchibhotla, 2016, Statistical Science.

Variable Selection : Empirical Bayes vs . Fully Bayes

Thomas S. Shively, William Jefferys, Wen Cui, 2002 .

Multiple-shrinkage principal component regression

E. George, S. Oman, 1996 .

Bayesian Regression Structure Discovery

Edward I. George, Robert E. McCulloch, Hugh A. Chipman, 2012 .

Bayesian Treed

Chipman, E. George, E. Robert, 2000 .

Heteroscedastic BART Using Multiplicative Regression Trees

Matthew Pratola, Hugh Chipman, Edward George, 2017, 1709.07542.

Misspecified Mean Function Regression: Making Good Use of Regression Models That Are Wrong

A. Buja, E. George, R. Berk, 2021 .

EMVS: The EM Approach to Bayesian Variable Selection

Veronika Rockova, Edward I. George, E. George, 2014 .

Variable Selection Inference for Bayesian Additive Regression Trees

Edward I. George, Shane T. Jensen, Adam Kapelner, 2013 .

The Conspiracy of Random Predictors and Model Violations against Classical Inference in Regression

Andreas Buja, Richard A. Berk, Kai Zhang, 2014 .

Models as Approximations --- Part II: A General Theory of Model-Robust Regression

Arun K. Kuchibhotla, A. Buja, L. Brown, 2016, 1612.03257.

Models as Approximations: How Random Predictors and Model Violations Invalidate Classical Inference in Regression

Andreas Buja, Richard A. Berk, Edward I. George, 2014 .

Models as Approximations — A Conspiracy of Random Predictors and Model Violations Against Classical Inference in Regression

A. Buja, L. Brown, E. George, 2014 .

What You Can Learn from Wrong Causal Models

Richard A. Berk, Emil Pitkin, Kai Zhang, 2013 .

High-dimensional nonparametric monotone function estimation using BART

Thomas S. Shively, Edward I. George, Robert E. McCulloch, 2016 .

A Basket-mix Model to Identify Cherry-picked Brands

Edward I. George, Leigh McAlister, E. George, 2009 .

Modeling DVD Preorder and Sales: An Optimal Stopping Approach

Edward I. George, Jehoshua Eliashberg, Sam K. Hui, 2008, Mark. Sci..

mBART: Multidimensional Monotone BART

Thomas S. Shively, Edward I. George, Robert E. McCulloch, 2016, Bayesian Analysis.

Extracting Representative Tree Models From a Forest

Edward I. George, Robert E. McCulloch, Hugh A. Chipman, 1998 .

Simultaneous Variable and Covariance Selection With the Multivariate Spike-and-Slab LASSO

Sameer K. Deshpande, E. George, V. Ročková, 2017, Journal of Computational and Graphical Statistics.

Spike-and-slab Lasso biclustering

Edward I. George, Veronika Ročková, Gemma E. Moran, 2021 .

Bayesian Penalty Mixing: The Case of a Non-separable Penalty

Veronika Rockova, Edward I. George, E. George, 2016 .

Dilution priors: Compensating for model space redundancy

Edward I. George, E. George, 2010 .

Optimal Shrinkage Estimation of Predictive Densities Under α-Divergences

E. George, Gourab Mukherjee, Keisuke Yano, 2021, Bayesian Analysis.

Two Approaches to Bayesian Model Selection with Applications

Edward I. George, Robert E. McCulloch, Ruey S. Tsay, 1996 .

Uncovering Patterns for Adverse Pregnancy Outcomes with Spatial Analysis: Evidence from Philadelphia

Silvia P. Canel'on, E. George, M. Boland, 2021, 2105.04981.

A Conspiracy of Random X and Model Violation against Classical Inference in Linear Regression

A. Buja, L. Brown, E. George, 2013 .

Journal of the American Statistical Association is currently published by American Statistical Association.

Ove Frank, E. George, R. McCulloch, 2007 .

MuSP: A multistep screening procedure for sparse recovery

E. George, Ji Zhu, Yuehan Yang, 2018, Stat.

Model Selection and estimation of Multi Screen Penalty

E. George, Ji Zhu, Yuehan Yang, 2018 .

Clustering Areal Units at Multiple Levels of Resolution to Model Crime in Philadelphia

Shane T. Jensen, E. George, Cecilia Balocchi, 2021, 2112.02059.

Bayesian Model Selection

E. George, 2006 .

Redefine statistical significance

Christopher D. Chambers, Felix D. Schönbrodt, Jeffrey N. Rouder, 2017, Nature Human Behaviour.

Models as Approximations: How Random Predictors and Model Violations Invalidate Classical Inference in Regression

A. Buja, L. Brown, E. George, 2014 .

Calibrated Percentile Double Bootstrap For Robust Linear Regression Inference

A. Buja, E. George, Linda H. Zhao, 2015, 1511.00273.

Measuring a Brand's Tendency to be Included in High Value Baskets

E. George, L. McAlister, Yung-Hsin Chien, 2001 .

Experiments Covariance Adjustments for the Analysis of Randomized Field

A. Buja, L. Brown, E. George, 2014 .

Model Uncertainty

M. Clyde, E. George, 2003 .

gBF: A Fully Bayes Factor with a Generalized g-prior

Edward I. George, Yuzo Maruyama, Yuzo Maruyama, 2008 .

Bayesian Stochastic Search for VAR Model Restrictions January 2005 , Revised November 2006

E. George, 2005 .

Calibration and Empirical Bayes Variable Selection

Dean Phillips Foster, A. U.S., E. George, 1997 .

SHRINKAGE DOMINATION IN A MULTIVARIATE COMMON MEAN PROBLEM

E. George, 1991 .

Stochastic Search Model Selection for Restricted VAR Models

Dongchu Sun, E. George, 2004 .

Bayesian treed response surface models

Robert B. Gramacy, Edward I. George, Robert E. McCulloch, 2013, WIREs Data Mining Knowl. Discov..

Edinburgh Research Explorer Redefine statistical significance

Felix D. Schönbrodt, Jeffrey N. Rouder, T. Cook, 2019 .

Ensemble of trees approaches to risk adjustment for evaluating a hospital’s performance

Dylan S. Small, E. George, M. Traskin, 2014, Health Care Management Science.

A Bayesian Model of Cycle Time Prediction

Christina Y.J. Chen, Edward I. George, Valerie Tardif, 2001 .

ADAPTIVE BAYESIAN CRITERIA IN VARIABLE SELECTION FOR GENERALIZED LINEAR MODELS

Edward I. George, Xinlei Wang, E. George, 2007 .