Department of Mathematics & Statistics
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Professor Richard Barker

Phone: 479-7756

** Left the Department in 2017 to become the Pro-Vice-Chancellor, Division of Sciences. **

Research Interests and student opportunities.

My recent research and those of current an recently completed graduate students include:

  • Bayesian inference for hierarchical models
  • Statistical theory, methods and analysis for applications in
  • Fisheries and wildlife ecology
  • Sport science and exercise physiology
  • Climate change
  • Theory and analysis of mark-recapture and radio-telemetry data

Current PhD and post-doc opportunities


BUGS code for mark-recapture models


Recent Publications

  • Barker, R. J., Schofield, M. R., Link, W. A., & Sauer, J. R. (2017). On the reliability of N-mixture models for count data. Biometrics. Advance online publication. doi: 10.1111/biom.12734
  • Bellingham, P. J., Richardson, S. J., Mason, N. W. H., Veltman, C. J., Allen, R. B., Allen, W. J., Barker, R. J., … Ramsey, D. S. L. (2016). Introduced deer at low densities do not inhibit the regeneration of a dominant tree. Forest Ecology & Management, 364, 70-76. doi: 10.1016/j.foreco.2015.12.013
  • Schofield, M., & Barker, R. (2016). 50-year-old curiosities: Ancillarity and inference in capture-recapture models. Statistical Science, 31(2), 161-174. doi: 10.1214/16-STS550
  • Schofield, M. R., Barker, R. J., Gelman, A., Cook, E. R., & Briffa, K. R. (2016). A model-based approach to climate reconstruction using tree-ring data. Journal of the American Statistical Association, 111(513), 93-106. doi: 10.1080/01621459.2015.1110524
  • Barker, R. J., & Link, W. A. (2015). Truth, models, model sets, AIC, and multimodel inference: A Bayesian perspective. Journal of Wildlife Management, 79(5), 730-738. doi: 10.1002/jwmg.890