Research Interests

My principal research interests lie in Bayesian inference, particularly MCMC methods and model selection, and the application and development of methods to environmental statistics. I am particularly interested in applications in linguistic change over time and applications in fault detection and visualisation of high frequency remote sensor data on environmental variables.


The code to fit some of the models in my research can be found here. This is currently under development so please contact me if you require further information.

Shiny Apps


Conference Precedings

  • C. Alexander, T. Neocleous, J. Stuart-Smith, L. Evers, Using chain graph models for structural inference with an application to linguistic data, Precedings of the 32nd International Workshop on Statistical Modelling, Groningen, Netherlands, pp 270-274,



  • The International Environmetrics Society Virtual Conference, 2020 Creating a Digital Environment - Developing the Digitally Enabled Environment to Understand Long-Term Environmental Change

  • Royal Statistical Society International Conference, University of Exeter, September 2015, Analysis of linguistic change in Glaswegian dialect using graphical models.


  • 13th Annual University of Glasgow Learning and Teaching Conference, University of Glasgow, August 2020, Study Design and Quantitative Analysis in Learning and Teaching Scholarship: Case Study Exploring Student Attitudes to Introductory Statistics

  • Royal Statistical Society International Conference, University of Cardiff, September 2018, Analysis of Linguistic Change Using Chain Graph Models for Structural Inference.

  • International Conference on Computational Statistics, Oviedo, August 2016, Application of chain graph models for structural inference on multi-level data.