David B. Dunson

Image of David B. Dunson

Arts and Sciences Professor of Statistical Science

Development of Bayesian methods motivated by applications with complex and high-dimensional data. A particular focus is on nonparametric Bayes approaches for conditional distributions and for flexible borrowing of information. I am also interested in methods for accommodating model uncertainty in hierarchical models, and in latent variable methods, including structural equation models. A recent interest has been in functional data analysis.

Appointments and Affiliations
  • Arts and Sciences Professor of Statistical Science
  • Professor of Statistical Science
  • Professor in the Department of Electrical and Computer Engineering
  • Faculty Network Member of the Duke Institute for Brain Sciences
Contact Information:
Education:

  • Ph.D. Emory University, 1997
  • B.S. Pennsylvania State University, 1994

Research Interests:

Development of Bayesian methods motivated by applications with complex and high-dimensional data. A particular focus is on nonparametric Bayes approaches for conditional distributions and for flexible borrowing of information. I am also interested in methods for accommodating model uncertainty in hierarchical models, and in latent variable methods, including structural equation models. A recent interest has been in functional data analysis.

Specialties:

Bayesian Statistics
Complex Hierarchical and Latent Variable Modelling
Nonparametric Statistical Modelling
Model Selection
Statistical Modeling

Courses Taught:
  • STA 360: Bayesian Inference and Modern Statistical Methods
  • STA 393: Research Independent Study
  • STA 601: Bayesian and Modern Statistical Data Analysis
  • STA 790: Special Topics in Statistics
  • STA 993: Independent Study
  • STA 994: Independent Study

Representative Publications: (More Publications)
    • Durante, D; Dunson, DB, Bayesian dynamic financial networks with time-varying predictors, Statistics and Probability Letters, vol 93 (2014), pp. 19-26 [10.1016/j.spl.2014.06.015] [abs].
    • Kundu, S; Dunson, DB, Latent factor models for density estimation, Biometrika, vol 101 no. 3 (2014), pp. 641-654 [10.1093/biomet/asu019] [abs].
    • Rodriguez, A; Dunson, DB, Functional clustering in nested designs: Modeling variability in reproductive epidemiology studies, Annals of Applied Statistics, vol 8 no. 3 (2014), pp. 1416-1442 [10.1214/14-AOAS751] [abs].
    • Dunson, DB, Comment, Journal of the American Statistical Association, vol 109 no. 507 (2014), pp. 890-891 [10.1080/01621459.2014.955988] [abs].
    • Wheeler, MW; Dunson, DB; Pandalai, SP; Baker, BA; Herring, AH, Mechanistic Hierarchical Gaussian Processes, Journal of the American Statistical Association, vol 109 no. 507 (2014), pp. 894-904 [10.1080/01621459.2014.899234] [abs].