Tilman Davies, Our people, Department of Mathematics and Statistics

(BCM (UWA), BScHons (Massey), PhD (Massey))

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:

STAT 110 Statistical Methods
STAT 260 Visualisation and Modelling in R
STAT 372 Stochastic Modelling
STAT 403 Case Studies in Statistics

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. (2025). Bandwidth selection for kernel intensity estimators for spatial point processes. Scandinavian Journal of Statistics. Advance online publication. doi: 10.1111/sjos.12782 Journal - Research Article

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, 56, 100759. 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

2025

Journal - Research Article

2023

Journal - Research Article

2022

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

Baddeley, A., Davies, T. M., Rakshit, S., Nair, G., & McSwiggan, G. (2022). Diffusion smoothing for spatial point patterns. Statistical Science, 37(1), 123-142. doi: 10.1214/21-STS825

Hazelton, M. L., & Davies, T. M. (2022). Pointwise comparison of two multivariate density functions. Scandinavian Journal of Statistics, 49, 1791-1810. doi: 10.1111/sjos.12565

2021

Journal - Research Article

Elson, R., Davies, T. M., Lake, I. R., Vivancos, R., Blomquist, P. B., Charlett, A., & Dabrera, G. (2021). The spatio-temporal distribution of COVID-19 infection in England between January and June 2020. Epidemiology & Infection, 149, e73. doi: 10.1017/s0950268821000534

Baddeley, A., Nair, G., Rakshit, S., McSwiggan, G., & Davies, T. M. (2021). Analysing point patterns on networks: A review. Spatial Statistics, 42, 100435. doi: 10.1016/j.spasta.2020.100435

2020

Journal - Research Article

Elson, R., Davies, T. M., Jenkins, C., Vivancos, R., O'Brien, S. J., & Lake, I. R. (2020). Application of kernel smoothing to estimate the spatio-temporal variation in risk of STEC O157 in England. Spatial & Spatio-temporal Epidemiology, 32, 100305. doi: 10.1016/j.sste.2019.100305

Conference Contribution - Verbal presentation and other Conference outputs

Davies, T. (2020, November). Keeping things running smoothly: A collection of kernel-based collaborations. Verbal presentation at the New Zealand Statistical Association (NZSA) Unconference, Auckland.

2019

Journal - Research Article

Davies, T. M., Schofield, M. R., Cornwall, J., & Sheard, P. W. (2019). Modelling multilevel spatial behaviour in binary-mark muscle fibre configurations. Annals of Applied Statistics, 13(3), 1329-1347. doi: 10.1214/18-AOAS1214

Rakshit, S., Davies, T., Moradi, M. M., McSwiggan, G., Nair, G., Mateu, J., & Baddeley, A. (2019). Fast kernel smoothing of point patterns on a large network using two-dimensional convolution. International Statistical Review, 87(3), 531-556. doi: 10.1111/insr.12327

Davies, T. M., & Lawson, A. B. (2019). An evaluation of likelihood-based bandwidth selectors for spatial and spatiotemporal kernel estimates. Journal of Statistical Computation & Simulation, 89(7), 1131-1152. doi: 10.1080/00949655.2019.1575066

Conference Contribution - Published proceedings: Abstract

Redmond, A. K., Davies, T. M., & Schofield, M. R. (2019). Hierarchical modelling for spatial muscle fibre configurations. Proceedings of the New Zealand Statistical Association Conference. (pp. 47). Retrieved from https://www.otago.ac.nz/nzsa/programme-and-speakers/

2018

Journal - Research Article

Davies, T. M., Flynn, C. R., & Hazelton, M. L. (2018). On the utility of asymptotic bandwidth selectors for spatially adaptive kernel density estimation. Statistics & Probability Letters, 138, 75-81. doi: 10.1016/j.spl.2018.02.067

Davies, T. M., Marshall, J. C., & Hazelton, M. L. (2018). Tutorial on kernel estimation of continuous spatial and spatiotemporal relative risk. Statistics in Medicine, 37(7), 1191-1221. doi: 10.1002/sim.7577

Davies, T. M., & Baddeley, A. (2018). Fast computation of spatially adaptive kernel estimates. Statistics & Computing, 28(4), 937-956. doi: 10.1007/s11222-017-9772-4

2016

Authored Book - Research

Davies, T. M. (2016). The book of R: A first course in programming and statistics. San Francisco, CA: No Starch Press, 832p.

Journal - Research Article

Davies, T. M., Jones, K., & Hazelton, M. L. (2016). Symmetric adaptive smoothing regimens for estimation of the spatial relative risk function. Computational Statistics & Data Analysis, 101, 12-28. doi: 10.1016/j.csda.2016.02.008

Journal - Professional & Other Non-Research Articles

Davies, T. M., Sheard, P. W., & Cornwall, J. (2016). Comment on Makino et al. and observations on spatial modeling. Anatomical Science International, 91(4), 423-424. doi: 10.1007/s12565-016-0347-9

2015

Journal - Research Article

Smith, B. A., Davies, T. M., & Higham, C. F. W. (2015). Spatial and social variables in the Bronze Age Phase 4 cemetery of Ban Non Wat, Northeast Thailand. Journal of Archaeological Science: Reports, 4, 362-370. doi: 10.1016/j.jasrep.2015.10.003

Fletcher, J. G. R., Stringer, M. D., Briggs, C. A., Davies, T. M., & Woodley, S. J. (2015). CT morphometry of adult thoracic intervertebral discs. European Spine Journal, 24(10), 2321-2329. doi: 10.1007/s00586-015-3925-y

Farrell, S. F., Davies, T. M., & Cornwall, J. (2015). Use of clinical anatomy resources by musculoskeletal outpatient physiotherapists in Australian Public Hospitals: A cross-sectional study. Physiotherapy Canada, 67(3), 273-279. doi: 10.3138/ptc.2014-38E

Taylor, B. M., Davies, T. M., Rowlingson, B. S., & Diggle, P. J. (2015). Bayesian inference and data augmentation schemes for spatial, spatiotemporal and multivariate log-Gaussian Cox processes in R. Journal of Statistical Software, 63(7). Retrieved from http://www.jstatsoft.org/v63/i07

Conference Contribution - Published proceedings: Abstract

Davies, T. M., Hill, P., & Summerby-Murray, D. (2015). Kernel density-ratio surfaces for estimation of geographical relative risk, with an application to pneumococcal disease and radiological pneumonia in The Gambia. Proceedings of the 8th Annual Otago International Health Research Network (OIHRN) Conference. (pp. 11). Retrieved from http://dnmeds.otago.ac.nz/departments/psm/research/international_hlth

2014

Conference Contribution - Published proceedings: Abstract

Cornwall, J., Davies, T., & Lees, D. (2014). Student injuries in the dissecting room. Clinical Anatomy, 27(8), (pp. 1359). doi: 10.1002/ca.22459

Farrell, S. F., Davies, T. M., & Cornwall, J. (2014). The use of clinical anatomy resources by musculoskeletal outpatient physiotherapists in New South Wales public hospitals. Clinical Anatomy, 27(8), (pp. 1352). doi: 10.1002/ca.22459

Cornwall, J., Davies, T., Louw, G., Zimanyi, M., Armstrong, S., Wetchateng, T., … Stringer, M. (2014). The demographic characteristics of body donors: An intercontinental study. Annals of Anatomy, 196(Suppl.), (pp. 225). doi: 10.1016/j.aanat.2014.05.035

2013

Journal - Research Article

Davies, T. M. (2013). Scaling oversmoothing factors for kernel estimation of spatial relative risk. Epidemiologic Methods, 2(1), 67-83. doi: 10.1515/em-2012-0008

Davies, T. M., & Bryant, D. J. (2013). On circulant embedding for Gaussian random fields in R. Journal of Statistical Software, 55(9). Retrieved from http://www.jstatsoft.org/v55/i09

Davies, T. M., & Hazelton, M. L. (2013). Assessing minimum contrast parameter estimation for spatial and spatiotemporal log-Gaussian Cox processes. Statistica Neerlandica, 67(4), 355-389. doi: 10.1111/stan.12011

Davies, T. M. (2013). Jointly optimal bandwidth selection for the planar kernel-smoothed density-ratio. Spatial & Spatio-temporal Epidemiology, 5, 51-65. doi: 10.1016/j.sste.2013.04.001

Davies, T. M., Cornwall, J., & Sheard, P. W. (2013). Modelling dichotomously marked muscle fibre configurations. Statistics in Medicine, 32(24), 4240-4258. doi: 10.1002/sim.5806

Cornwall, J., Davies, T. M., & Lees, D. (2013). Student injuries in the dissecting room. Anatomical Sciences Education, 6(6), 404-409. doi: 10.1002/ase.1363

Taylor, B. M., Davies, T. M., Rowlingson, B. S., & Diggle, P. J. (2013). lgcp: Inference with spatial and spatio-temporal log-Gaussian Cox processes in R. Journal of Statistical Software, 52(4). Retrieved from http://www.jstatsoft.org/v52/i04

Conference Contribution - Published proceedings: Abstract

Davies, T. (2013). Jointly optimal bandwidth selection for the planar kernel-smoothed density-ratio. Proceedings of the Joint New Zealand Statistical Association (NZSA) and Operations Research Society of New Zealand (ORSNZ) Conference: Analytics for a Changing World: From Data to Decisions. (pp. 53). Retrieved from https://secure.orsnz.org.nz/conf47/index.php

Davies, T. M., Sheard, P. W., & Cornwall, J. (2013). Development of a novel statistical method to test spatial distribution of skeletal muscle fiber types. Clinical Anatomy, 26, (pp. 643). doi: 10.1002/ca.22235

2012

Journal - Research Article

Zhang, Z., Chen, D., Chen, Y., Davies, T. M., Vaillancourt, J.-P., & Liu, W. (2012). Risk signals of an influenza pandemic caused by highly pathogenic avian influenza subtype H5N1: Spatio-temporal perspectives. Veterinary Journal, 192(3), 417-421. doi: 10.1016/j.tvjl.2011.08.012

2011

Journal - Research Article

Davies, T. M., Hazelton, M. L., & Marshall, J. C. (2011). sparr: Analyzing spatial relative risk using fixed and adaptive kernel density estimation in R. Journal of Statistical Software, 39(1). Retrieved from http://www.jstatsoft.org/v39/i01/paper

Sanson, R. L., Harvey, N., Garner, M. G., Stevenson, M. A., Davies, T. M., Hazelton, M. L., … Owen, K. (2011). Foot and mouth disease model verification and 'relative validation' through a formal model comparison. Revue Scientifique et Technique, 30(2), 527-540. doi: 10.20506/rst.30.2.2051

Conference Contribution - Poster Presentation (not in published proceedings)

Diggle, P., Taylor, B., Davies, T., & Rowlingson, B. (2011, March-April). Bayesian parameter estimation for the log-Gaussian Cox process. Poster session presented at the Inference For Epidemic-related Risk (InFER), Warwick, UK.

2010

Journal - Research Article

Davies, T. M., & Hazelton, M. L. (2010). Adaptive kernel estimation of spatial relative risk. Statistics in Medicine, 29(23), 2423-2437. doi: 10.1002/sim.3995

2009

Journal - Research Article

Hazelton, M. L., & Davies, T. M. (2009). Inference based on kernel estimates of the relative risk function in geographical epidemiology. Biometrical Journal, 51(1), 98-109. doi: 10.1002/bimj.200810495

Conference Contribution - Verbal presentation and other Conference outputs

Davies, T. (2009, September). On adaptive kernel estimates of spatially dependent disease risk. Verbal presentation at the New Zealand Statistical Association Conference, Wellington, New Zealand.