Daniel Henderson


My research involves developing statistical models and methodology to analyse data arising from a variety of application areas (such as, but not limited to, biology, archaeology, engineering and sport). I am also interested in developing efficient computational algorithms to fit these models. Some examples of my research interests are given below.

Bradley and Terry playing for the Celtics

Sports analytics

Previous work has involved forecasting Formula One results, in-play forecasting of football match outcomes, and analysing paired comparison data in sports such as football, tennis and basketball via Bradley-Terry type models (hence the picture!).

Selected publications

Johnson, S. R., Henderson, D. A. and Boys, R. J. (2019+) Revealing subgroup structure in ranked data using a Bayesian WAND. Journal of the American Statistical Association (Theory and Methods). [arxiv | github]

Wilson, K. J., Henderson, D. A. and Quigley, J. (2018) Emulation of utility functions over a set of permutations: sequencing reliability growth tasks. Technometrics, 60, 273-285. [arxiv]

Henderson, D. A. and Kirrane, L. J. (2018) A comparison of truncated and time-weighted Plackett-Luce models for probabilistic forecasting of Formula One results. Bayesian Analysis, 13, 335-358. [github]

Sherlock, C., Golightly, A. and Henderson, D.A. (2017) Adaptive, delayed-acceptance MCMC for targets with expensive likelihoods. Journal of Computational and Graphical Statistics, 26, 434-444. [arxiv]

Golightly, A., Henderson, D.A., and Sherlock, C. (2015) Delayed acceptance particle MCMC for exact inference in stochastic kinetic models. Statistics and Computing, 25, 1039-1055. [arxiv]

Henderson, D. A., Boys, R. J. and Wilkinson, D. J. (2010) Bayesian calibration of a stochastic kinetic computer model using multiple data sources. Biometrics, 66, 249-256. [Supplementary material]

Jones, M. C. and Henderson, D. A. (2009) Maximum likelihood kernel density estimation: on the potential of convolution sieves. Computational Statistics and Data Analysis, 53, 3726-3733. (The supporting technical report cited in this paper is available here.)

Henderson, D. A., Boys, R. J., Krishnan, K. J., Lawless, C. and Wilkinson, D. J. (2009) Bayesian emulation and calibration of a stochastic computer model of mitochondrial DNA deletions in substantia nigra neurons. Journal of the American Statistical Association, 104, 76-87. [Supplementary material]

Jones, M. C. and Henderson, D. A. (2007) Kernel-type density estimation on the unit interval. Biometrika, 94, 977-984. (The supporting technical report cited in this paper is available here.)

Further details are available on my Google Scholar page.



Jack Kennedy (2018- ) Elicitation and prior specification for uncertainty analysis in large complex energy systems models (PhD). Supervised jointly with Kevin Wilson.

Josh Cowley (2019- ) Real time monitoring of groundwater monitoring networks using telemetry (PhD). Supervised jointly with Colin Gillespie. Partly funded by Shell.

Cleo Bamber (2019-2020) Predicting time spent in different areas of the pitch in a football match (MMathStat). In collaboration with Smartodds.


Muhammad Irfan bin Abdul Jalal (2015-2019) Bayesian Survival Analysis With Missing Data Using Integrated Nested Laplace Approximation (PhD). Main supervisor: Malcolm Farrow.

Stephen Johnson (2014-2018) Bayesian modelling and analysis of ranked data (PhD). Supervised jointly with Richard Boys. Stephen is currently a postdoctoral research associate at Newcastle University.

Rachel Binks (2018-2019) Bayesian nonparametric models for variable selection in regression (MMathStat).

Jordan Coupland (2018-2019) Newcastle Falcons data analytics (MMathStat). In collaboration with Joe Kupusarevic (Newcastle Falcons).

Josh Cowley (2018-2019) Bayesian inference for nonhomogeneous Poisson Processes with applications to modelling football event data (MMathStat).

Rowan South (2016-2017) In-play forecasting of Premier League odds (MMathStat).

Louis Willsher (2016-2017) Determining player impact in the NBA (MMathStat).

Nathan Wood (2015-2016) Bayesian inference for mixture models (MMathStat).

Yasmin Jowsey (2015-2016) Bayesian analysis of paired comparison data using Stern's model (MMathStat).

Mac Misiura (2014-2015) Bayesian analysis of paired comparison data (MMathStat).

Liam Kirrane (2013-2014) Bayesian inference for ranking models applied to Formula One Data (MMathStat).

Rebecca Bulmer (2012-2013) Bayesian inference for generalised Bradley-Terry models (MMathStat).

Teaching & Admin

In 2019-20 I'm teaching the following modules.

  • MAS2902 Introduction to Regression and Stochastic Modelling
  • MAS2403 Statistical Methods for Marketing & Management
  • MAS8951Modern Bayesian Inference

My time is also spent on several administrative roles within the School of Mathematics, Statistics and Physics, including:

  • Teaching and Curriculum Coordinator (TCC) for Statistics
  • Degree Programme Director for BSc Mathematics & Economics (GL11) and BSc Mathematics & Accounting (NG41)
  • JH advisor (Mathematics & Psychology)
  • Major-Minor advisor
  • Personal tutor
  • Summer Internship Coordinator

Contact Information

Dr D. A. Henderson
School of Mathematics, Statistics & Physics
Newcastle University
Newcastle upon Tyne

Office: 2.21, Herschel Building
Telephone: +44 (0)191 208 7246
E-mail: daniel.henderson(at)ncl.ac.uk
Profile: Official