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College of Arts & Sciences
Department of Statistics


Bayesian Statistics

Bayesian statistics and Bayesian nonparametrics

[Markov chain Monte Carlo, graphical models, hierarchical models, nonparametric priors, objective priors]

 

Primary Theme: Tim Hanson, Xiaoyan Lin, Lianming Wang

Secondary Theme: Habing, Lynch, Tebbs

Some Publications

  • X. Lin, D. Sun, P. L. Speckman, and J. N. Rouder (2013). “Existence of MLE and posteriors for a recognition-memory model.” Statistics and Probability Letters, 83, 2415- 2421.
  • D. Banks, G. Datta, A. Karr, J. Lynch, J. Niemi and F. Vera (2012). Bayesian CAR Models for Syndromic Surveillance on Multiple Data Streams: Theory and Practice,” Information Fusion, 13 (2012) 105–116.
  • M. J. Heaton, D. Banks, J. Zou, Alan F. Karr, G. Datta, J. Lynch and F. Vera (2012). A Spatio-Temporal Absorbing State Model for Disease and Syndromic Surveillance. Statist. Med, 31 2123–2136.
  • Zou, Alan F. Karr, D. Banks, M. J. Heaton, G. Datta, J. Lynch and F. Vera (2012). Bayesian Methodology for the Analysis of Spatial–Temporal Surveillance Data, Statistical Analysis and Data Mining, 5, 194–204.
  • Hanson, T., Monteiro, J., and Jara, A. (2011). The Polya tree sampler: Towards efficient and automatic independent Metropolis-Hastings proposals. Journal of Computational and Graphical Statistics, 20, 41-62.
  • Pritchard, N. and Tebbs, J. (2011). Bayesian inference for disease prevalence using negative binomial group testing. Biometrical Journal, 53, 40-56.
  • X. Lin and D. Sun (2010). “A Note on the Existence of the Posteriors for One-way Random Effect Probit Models.” Statistics and Probability Letters, 80, 57-62.
  • L. Wang and D. Dunson (2010). Semiparametric Bayes Multiple testing: Application to Tumor Data . Biometrics, 66, 493-501.
  • H. Wang and M. West (2009), Bayesian analysis of matrix normal graphical models. Biometrika 96:821-834
  • H. Wang and C. M. Carvalho (2010), Simulation of Hyper-Inverse Wishart Distributions for Non-decomposable Graphs. Electronic Journal of Statistics 4:1470-1467
  • L. Wang and D. Dunson (2011). Fast Bayesian Inference in Dirichlet Process Mixture Models . Journal of Computational and Graphical Statistics, 20, 196.216.
  • Zhao, L., Hanson, T., and Carlin, B. (2009). Flexible spatial frailty modeling via mixtures of Polya trees. Biometrika, 96, 263-276.
  • Branscum, A. and Hanson, T. (2008). Bayesian nonparametric meta-analysis using Polya tree mixture models. Biometrics, 64, 825-833.
  • Hanson, T. (2006). Inference for mixtures of finite Polya tree models. Journal of the American Statistical Association, 101, 1548-1565.
  • Christensen, R., Johnson, W., Branscum, A., and Hanson, T. (2010). Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians. CRC Press, Boca Raton.
  • Agresti, A. and Hitchcock, D. B. (2005), "Bayesian Inference for Categorical Data Analysis," Statistical Methods and Applications: Journal of the Italian Statistical Society, 14, 297-330.