Professor Chris Sherlock
Professor of StatisticsResearch Interests
- MCMC theory, methodology and application
- Stochastic processes (SDEs and hidden Markov models)
- Spatial statistics and veterinary epidemiology
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PhD Supervision Interests
Projects are available in combinations of (1) MCMC theory: efficiency as a function of tuning parameters, and convergence; (2) MCMC methodology: developing new algorithms or variations on existing algorithms; (3) MCMC applications in e.g. the environment, ecology or epidemiology; (4) particle filters and bridges for stochastic processes. Example MCMC areas include: pseudo-marginal, delayed acceptance, HMC, non-reversible, and MCMC and variations for tall data.
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STOR-i : Predicting Recruitment to Clinical Trials
01/10/2018 → 31/03/2022
Research
Bayesian and Computational Statistics
STOR-i Centre for Doctoral Training
- Bayesian and Computational Statistics
- Environmental and Ecological Statistics
- STOR-i Centre for Doctoral Training