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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

  • Schofield, M. R., Barker, R. J., & Gelling, N. (2018). Continuous-time capture—recapture in closed populations. Biometrics, 74(2), 626-635. doi: 10.1111/biom.12763
  • Link, W. A., Schofield, M. R., Barker, R. J., & Sauer, J. R. (2018). On the robustness of N-mixture models. Ecology, 99(7), 1547-1551. doi: 10.1002/ecy.2362
  • Barker, R. J., Schofield, M. R., Link, W. A., & Sauer, J. R. (2018). On the reliability of N-mixture models for count data. Biometrics, 74(1), 369-377. doi: 10.1111/biom.12734
  • Schofield, M. R., & Barker, R. J. (2017). Model fitting and evaluation in climate reconstruction of tree-ring data: A comment on Steinschneider et al. (2017): Hierarchical regression models for dendroclimatic standardization and climate reconstruction. Dendrochronologia, 46, 77-84. doi: 10.1016/j.dendro.2017.10.004
  • 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