James O. Berger

James O. Berger

Arts and Sciences Professor of Statistics

External address: 
221 Old Chemistry, Durham, NC 27708
Internal office address: 
Box 90251, Durham, NC 27708-0251
Phone: 
(919) 684-4531

Selected Grants

Collaborative Research: Using Precursor Information to Update Probabilistic Hazard Maps awarded by National Science Foundation (Co Investigator). 2018 to 2020

Hazards SEES: Persistent volcanic crises -- resilience in the face of prolonged and uncertain risk awarded by State University of New York - Buffalo (Co-Principal Investigator). 2015 to 2019

Bayesian Analysis and Interfaces awarded by National Science Foundation (Principal Investigator). 2014 to 2019

Collaborative Research: Statistical And Computational Models and Methods for Extracting Knowledge from Massive Disparate awarded by National Science Foundation (Co-Principal Investigator). 2012 to 2015

Collaborative Research: Bayesian Analysis and Applications awarded by National Science Foundation (Principal Investigator). 2010 to 2015

Hazards SEES Type 1: Persistent volcanic crises in the USA: from precursors to resilience awarded by University of Hawaii System (Co-Principal Investigator). 2013 to 2015

Bayes 250 Conference awarded by National Science Foundation (Principal Investigator). 2013 to 2014

Statistical and Applied Mathematical Sciences Institute (Supplement) awarded by National Science Foundation (Principal Investigator). 2002 to 2012

FRG: Collaborative Research: Prediction and Risk of Extreme Events Utilizing Mathematical Computer Models of Geophysical awarded by National Science Foundation (Co-Principal Investigator). 2008 to 2012

Pages

Bernardo, J. M., et al. Preface. Vol. 9780199694587, 2012. Scopus, doi:10.1093/acprof:oso/9780199694587.002.0004. Full Text

Berger, J. O. “Bayesian analysis: A look at today and thoughts of tomorrow.” Statistics in the 21st Century, 2001, pp. 275–90.

Benjamin, D. J., and J. O. Berger. “Three Recommendations for Improving the Use of p-Values.” American Statistician, vol. 73, no. sup1, Mar. 2019, pp. 186–91. Scopus, doi:10.1080/00031305.2018.1543135. Full Text

Berger, J. O., and L. A. Smith. “On the statistical formalism of uncertainty quantification.” Annual Review of Statistics and Its Application, vol. 6, Mar. 2019, pp. 433–60. Scopus, doi:10.1146/annurev-statistics-030718-105232. Full Text

Kyzyurova, K. N., et al. “Coupling computer models through linking their statistical emulators.” Siam Asa Journal on Uncertainty Quantification, vol. 6, no. 3, Jan. 2018, pp. 1151–71. Scopus, doi:10.1137/17M1157702. Full Text

Benjamin, Daniel J., et al. “Redefine statistical significance..” Nature Human Behaviour, vol. 2, no. 1, Jan. 2018, pp. 6–10. Epmc, doi:10.1038/s41562-017-0189-z. Full Text Open Access Copy

Gu, M., et al. “Robust Gaussian stochastic process emulation.” Annals of Statistics, vol. 46, no. 6A, Jan. 2018, pp. 3038–66. Scopus, doi:10.1214/17-AOS1648. Full Text

Gu, M., and J. O. Berger. “Parallel partial Gaussian process emulation for computer models with massive output.” Annals of Applied Statistics, vol. 10, no. 3, Sept. 2016, pp. 1317–47. Scopus, doi:10.1214/16-AOAS934. Full Text

Bayarri, M. J., et al. “Rejection odds and rejection ratios: A proposal for statistical practice in testing hypotheses..” Journal of Mathematical Psychology, vol. 72, June 2016, pp. 90–103. Epmc, doi:10.1016/j.jmp.2015.12.007. Full Text

Wang, X., and J. O. Berger. “Estimating shape constrained functions using Gaussian processes.” Siam Asa Journal on Uncertainty Quantification, vol. 4, no. 1, Jan. 2016, pp. 1–25. Scopus, doi:10.1137/140955033. Full Text

Berger, J. O., et al. “Overall objective priors.” Bayesian Analysis, vol. 10, no. 1, Mar. 2015, pp. 189–221. Scopus, doi:10.1214/14-BA915. Full Text

Pages

Bernardo, J. M., et al. “Bayesian Statistics 9.” Bayesian Statistics 9, vol. 9780199694587, 2012, pp. 1–720. Scopus, doi:10.1093/acprof:oso/9780199694587.001.0001. Full Text

Bayarri, M. J., et al. “Incorporating uncertainties into traffic simulators.” Recent Advances in Modeling and Simulation Tools for Communication Networks and Services, 2007, pp. 331–47.

Berger, James. “A statistician's perspective on Astrostatistics.” Statistical Challenges in Modern Astronomy Iv, edited by G. J. Babu and E. D. Feigelson, vol. 371, ASTRONOMICAL SOC PACIFIC, 2007, pp. 373–81.

Berger, J. O., and G. Molina. “Some recent developments in Bayesian variable selection.” Bayesian Inference and Maximum Entropy Methods in Science and Engineering, edited by R. Fischer et al., vol. 735, AMER INST PHYSICS, 2004, pp. 417–28.

Berger, J. O., and A. Connors. “Some recent developments in Bayesian analysis, with astronomical illustrations.” Statistical Challenges in Modern Astronomy Ii, edited by G. J. Babu and E. D. Feigelson, SPRINGER-VERLAG, 1997, pp. 15–48.

WANG, Y., et al. “A Bayesian testing procedure with valid conditional frequentist interpretation.” American Statistical Association 1994 Proceedings of the Section on Bayesian Statistical Science, AMER STATISTICAL ASSOC, 1994, pp. 187–95.

BERGER, J. O. “THE PRESENT AND FUTURE OF BAYESIAN MULTIVARIATE-ANALYSIS.” Multivariate Analysis: Future Directions, edited by C. R. Rao, vol. 5, ELSEVIER SCIENCE PUBL B V, 1993, pp. 25–53.

Berger, James O., et al. Bayesian Model Selection and Analysis for Cepheid Star Oscillations. Springer-Verlag, pp. 71–88. Crossref, doi:10.1007/0-387-21529-8_5. Full Text