James G. Scott
James G. Scott
Professor of Statistics and Data Science, University of Texas at Austin
Verified email at mccombs.utexas.edu - Homepage
Cited by
Cited by
The horseshoe estimator for sparse signals
CM Carvalho, NG Polson, JG Scott
Biometrika 97 (2), 465-480, 2010
Bayesian inference for logistic models using Polya-Gamma latent variables
NG Polson, JG Scott, J Windle
Journal of the American Statistical Association, 2013
Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem
JG Scott, JO Berger
The Annals of Statistics, 2587-2619, 2010
An exploration of aspects of Bayesian multiple testing
JG Scott, JO Berger
Journal of statistical planning and inference 136 (7), 2144-2162, 2006
Shrink globally, act locally: Sparse Bayesian regularization and prediction
NG Polson, JG Scott
Bayesian statistics 9 (501-538), 105, 2010
On the half-Cauchy prior for a global scale parameter
NG Polson, JG Scott
Bayesian Analysis, Arxiv preprint arXiv:1104, 2012
Handling sparsity via the horseshoe
CM Carvalho, NG Polson, JG Scott
Artificial Intelligence and Statistics, 73-80, 2009
Feature-inclusion stochastic search for Gaussian graphical models
JG Scott, CM Carvalho
Journal of Computational and Graphical Statistics, 2008
Objective Bayesian model selection in Gaussian graphical models
CM Carvalho, JG Scott
Biometrika 96 (3), 497-512, 2009
No control genes required: Bayesian analysis of qRT-PCR data
MV Matz, RM Wright, JG Scott
PloS one 8 (8), e71448, 2013
Requests for abortion in Latin America related to concern about Zika virus exposure
ARA Aiken, JG Scott, R Gomperts, J Trussell, M Worrell, CE Aiken
New England Journal of Medicine 375 (4), 396-398, 2016
Local shrinkage rules, Levy processes, and regularized regression
NG Polson, JG Scott
Journal of the Royal Statistical Society: Series B 74 (2), 287-311, 2012
The bayesian bridge
NG Polson, JG Scott, J Windle
Journal of the Royal Statistical Society: Series B: Statistical Methodology …, 2014
Inverting Color-Magnitude Diagrams to Access Precise Star Cluster Parameters: A Bayesian Approach
T von Hippel, WH Jefferys, J Scott, N Stein, DE Winget, S DeGennaro, ...
The Astrophysical Journal 645 (2), 1436, 2006
Proximal algorithms in statistics and machine learning
NG Polson, JG Scott, BT Willard
Statistical Science 30 (4), 559-581, 2015
False discovery rate regression: an application to neural synchrony detection in primary visual cortex
JG Scott, RC Kelly, MA Smith, P Zhou, RE Kass
Journal of the American Statistical Association 110 (510), 459-471, 2015
Fully Bayesian inference for neural models with negative-binomial spiking
J Pillow, J Scott
Advances in neural information processing systems 25, 1898-1906, 2012
Respiratory virus transmission dynamics determine timing of asthma exacerbation peaks: Evidence from a population-level model
RM Eggo, JG Scott, AP Galvani, LA Meyers
Proceedings of the National Academy of Sciences 113 (8), 2194-2199, 2016
Modeling unobserved heterogeneity using finite mixture random parameters for spatially correlated discrete count data
P Buddhavarapu, JG Scott, JA Prozzi
Transportation Research Part B: Methodological 91, 492-510, 2016
Factors influencing the likelihood of instrumental delivery success
CE Aiken, AR Aiken, JC Brockelsby, JG Scott
Obstetrics and gynecology 123 (4), 796, 2014
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