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(BCM (UWA), BScHons (Massey), PhD (Massey))Tilman Davies(2022)

Senior Lecturer
Director of Studies for 100-level Statistics
Pacific Island Liaison

Office: Science III, room 222
Tel +64 3 479 7772
Email tilman.davies@otago.ac.nz

About

Originally from Perth, Western Australia, I completed my doctoral degree at Massey University in 2011 before joining Otago. I've spent time living and working overseas, including stints in Denmark and the United States. My research has been supported by Marsden Fund grants and involves collaborators in industry and academia both here in New Zealand and internationally. I am the author of The Book of R, which I use for an introductory R workshop here at Otago.

For further details, please visit my personal website

Teaching responsibilities

My teaching responsibilities include:

Research Interests

I'm primarily interested in the smoothing and applied modelling of planar point patterns in space and space-time. Recent collaborations have also piqued an interest in developing Bayesian models for spatially varying phenomena.

My areas of research include:

  • Kernel smoothing and density-ratios
  • Computational statistics, R programming
  • Planar point patterns, spatial statistics, geostatistics
  • Applications in geographical epidemiology and biology

If you have a strong academic record and are interested in working with me as a postgraduate student on topics related to the above, get in touch.

Publications

Macdonald, B. J., Davies, T. M., & Hazelton, M. L. (2023). Feasibility of Monte-Carlo maximum likelihood for fitting spatial log-Gaussian Cox processes. Spatial Statistics. Advance online publication. doi: 10.1016/j.spasta.2023.100759 Journal - Research Article

Redmond, A. K., Davies, T. M., Schofield, M. R., & Sheard, P. W. (2023). New tools for the investigation of muscle fiber-type spatial distributions across histological sections. Skeletal Muscle, 13, 7. doi: 10.1186/s13395-023-00316-0 Journal - Research Article

Davies, T. M., Banerjee, S., Martin, A. P., & Turnbull, R. E. (2022). A nearest-neighbour Gaussian process spatial factor model for censored, multi-depth geochemical data. Journal of the Royal Statistical Society: Series C, 71, 1014-1043. doi: 10.1111/rssc.12565 Journal - Research Article

Baddeley, A., Davies, T. M., Hazelton, M. L., Rakshit, S., & Turner, R. (2022). Fundamental problems in fitting spatial cluster process models. Spatial Statistics, 52, 100709. doi: 10.1016/j.spasta.2022.100709 Journal - Research Article

Crump, J. A., & Davies, T. M. (2022). Towards equitable scheduling of global health teleconferences: A spatial exploration of the world's population and health by time zone. BMJ Open, 12, e056696. doi: 10.1136/bmjopen-2021-056696 Journal - Research Article

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