Google Scholar profile.

Current

  • A.Golightly and C.Sherlock; Efficient sampling of conditioned Markov jump processes [arXiv]
  • C.Sherlock; Simple, fast and accurate evaluation of the action of the exponential of a rate matrix on a probability vector. [arXiv] [code]
  • R.Towe, J.Tawn, R.Lamb and C.Sherlock; Model-based inference of conditional extreme value distributions with hydrological applications; submitted [arXiv]
  • S.Taylor, C.Sherlock, G.Ridall and P.Fearnhead; Motor Unit Number Estimation via Sequential Monte Carlo; submitted [arXiv].
  • C.Sherlock and A.Thiery; A discrete bouncy particle sampler; draft [arXiv]. [Newton Institute talk]
  • C.Sherlock and A.Lee; Variance bounding of delayed-acceptance kernels; submitted [arXiv].
  • S.Malory and C.Sherlock; Residual-bridge constructs for conditioned diffusions; submitted [arXiv].
  • C.Sherlock, A.Thiery and A.Golightly; Optimisation of delayed-acceptance pseudo-marginal random walk Metropolis algorithms; submitted [arXiv].


Journals

  • 2018 C.Nemeth and C.Sherlock; Merging MCMC subposteriors through Gaussian-process approximations; Bayesian Analysis 13(2), 507-530. [arXiv] [BA].
  • 2017 C.Sherlock, A.Thiery and A.Lee; Pseudo-marginal Metropolis-Hastings using averages of unbiased estimators; Biometrika 2017 asx031. doi: 10.1093/biomet/asx031. [arXiv]; [Biometrika].
  • 2017 G.A.Whitaker, A.Golightly, R.J.Boys and C.Sherlock; Improved bridge constructs for stochastic differential equations; Statistics and Computing 27 (4) 885--900. doi:10.1007/s11222-016-9660-3. [arXiv]; [StCo].
  • 2017 G.A.Whitaker, A.Golightly, R.J.Boys and C.Sherlock; Bayesian inference for diffusion-driven mixed-effects models; Bayesian Analysis 12(2) 435--463. doi:10.1214/16-BA1009. [arXiv]; [BA].
  • 2017 C.Sherlock, A.Golightly and D.Henderson; Adaptive, delayed-acceptance MCMC for targets with expensive likelihoods; JCGS 26 434-444. doi:10.1080/10618600.2016.1231064 [arXiv]; [JCGS].
  • 2016 C.Nemeth, C.Sherlock and P.Fearnhead; Particle Metropolis adjusted Langevin algorithms; Biometrika, 103 (3); 701--717. doi:10.1093/biomet/asw020 [arXiv]; [Biometrika].
  • 2016 (o/l 2015) C.Sherlock; Optimal scaling for the pseudo-marginal random walk Metropolis: insensitivity to the noise generating mechanism; MCAP 18(3), 869--884, 10.1007/s11009-015-9471-6. [arXiv].
  • 2015 A.Golightly, D.Henderson, C.Sherlock; Delayed acceptance particle MCMC for exact inference in stochastic kinetic models; Statistics and Computing 25 (5), 1039-1055. [arXiv]
  • 2015 C.Sherlock, A.Thiery, G.O.Roberts, J.S.Rosenthal; On the efficiency of pseudo-marginal random walk Metropolis algorithms; The Annals of Statistics, 43 (1), 238-275. [arXiv]
  • 2015 J. Lunn, C. Lewis, C.Sherlock; Impaired performance on advanced theory of mind tasks in children with epilepsy is related to poor communication and increased attention problems; Epilepsy and Behaviour 43 (2015) 109-116.
  • 2014 D.C. Archer, C. Sherlock, D. Costain; An investigation into the effects of horse age, time and geographical variation on IFEE risk: a nested case-control study; PLOS ONE 10.1371/journal.pone.0112072 (2014) .
  • 2014 C.Sherlock, A.Golightly, C.Gillespie; Bayesian inference for hybrid discrete-continuous stochastic kinetic models.; Inverse Problems, 30 (2014) 114005. [arXiv]
  • 2014 P.Fearnhead, V.Giagos, C.Sherlock; Inference for reaction networks using the Linear Noise Approximation.; Biometrics, 70, 457-466. [arXiv]
  • 2014 T.Xifara, C.Sherlock, S.Livingstone, S.Byrne, M.Girolami; Langevin diffusions and the Metropolis-adjusted Langevin algorithm ; Statistics and Probability Letters, 91, 14-19. [arXiv]
  • 2013 C.Sherlock, T.Xifara, S.Telfer, M.Begon; A hidden Markov model for disease interactions in a host; Journal of the Royal Statistical Society, Series C, 62(4), 609-627. [arXiv]
  • 2013 C. Sherlock; Optimal scaling of the random walk Metropolis: general criteria for the 0.234 acceptance rule; Journal of Applied Probability 50, 1-15. [Euclid];[poster pdf]
  • 2012 C. Sherlock and D. Elton; A class of spherical and elliptical distributions with Gaussian-like limit properties; Journal of Probability and Statistics 2012. Open Access. Doi:10.1155/2012/467187
  • 2012 R. Cox, T. Su, H. Clough, M.J. Woodward and C. Sherlock; Spatial and temporal patterns in antimicrobial resistance of Salmonella Typhimurium amongst cattle in England and Wales; Epidemiology and Infection 140(11), 2062-2073.
  • 2011 Williams, N.J., Sherlock C., Jones, T.R., Clough, H.E., Telfer, S.E., Begon, M., French, N.P., Bennett, M., and Hart, C.A.; The prevalence of antimicrobial resistant Escherichia coli in sympatric wild rodents varies by season and host; Journal of Applied Microbiology 110(4), 962-970. [statistical appendix]
  • 2010 C. Sherlock, P. Fearnhead, G. Roberts; The random walk Metropolis: linking theory and practice through a case study; Statistical Science 25(2), 172-190. [arXiv]
  • 2009 C. Sherlock, G. Roberts; Optimal scaling of the random walk Metropolis on elliptically symmetric unimodal targets; Bernoulli 15(3), 774-798. [arXiv]
  • 2006 P. Fearnhead, C. Sherlock; An exact Gibbs sampler for the Markov modulated Poisson process. Journal of the Royal Statistical Society, Series B. 68(5), pp767-784. [pdf] Details and Data.


Comments, contributions and conference articles

  • S. Sharples, D. Costain and C. Sherlock (2013); Predicting future offending in adolescents from a longitudinal survey with missing responses. In Proceedings of the 28th International Workshop on Statistical Modelling. (Eds: Muggeo, Capursi, Boscaino and Lovison).
  • S. Taylor, G. Ridall, C. Sherlock, P.Fearnhead (2013); Particle learning approach to Bayesian model selection: an application from neurology. In the Proceedings of the BAYSM conference in the series Springer Proceedings in Mathematics and Statistics. [pdf]
  • P. Fearnhead, V. Giagos, C. Sherlock (2011); Comment on: Parameter inference for stochastic kinetic models of bacterial gene regulation: a Bayesian approach to systems biology., Bayesian Statistics 9, the Valencia 9 conference proceedings, Oxford University Press.
  • C. Sherlock, P. Fearnhead (2007); Comment on: Estimating the Integrated Likelihood via Posterior Simulation Using the Harmonic Mean Identity, Bayesian Statistics 8, the Valencia 8 conference proceedings, Oxford University Press.
  • C. Sherlock (2005); Contribution to discussion of Bayesian analysis of single-molecule experimental data, JRSS Series C 54, 500.

PhD Thesis

  • C. Sherlock; Methodology for inference on the Markov modulated Poisson process and theory for optimal scaling of the random walk Metropolis, PhD Thesis, Lancaster University. [pdf]