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Professor Chris Sherlock

Senior Lecturer

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  1. Unpublished

    Methodology for inference on the Markov modulated Poisson process and theory for optimal scaling of the random walk Metropolis

    Sherlock, C., 2006, (Unpublished) Lancaster University. 245 p.

    Research output: Thesis › Doctoral Thesis

  2. Published

    Model-based inference of conditional extreme value distributions with hydrological applications

    Towe, R. P., Tawn, J. A., Lamb, R. & Sherlock, C. G., 1/12/2019, In: Environmetrics. 30, 8, 20 p., e2575.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  3. Published

    Motor unit number estimation via sequential Monte Carlo

    Taylor, S., Sherlock, C., Ridall, G. & Fearnhead, P., 1/04/2020, In: Computational Statistics and Data Analysis. 144, 16 p., 106845.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  4. Published

    On the efficiency of pseudo-marginal random walk Metropolis algorithms

    Sherlock, C., Thiery, A., Roberts, G. & Rosenthal, J., 01/2015, In: Annals of Statistics. 43, 1, p. 238-275 38 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  5. Published

    Optimal scaling for the pseudo-marginal random walk Metropolis: insensitivity to the noise generating mechanism

    Sherlock, C., 09/2016, In: Methodology and Computing in Applied Probability. 18, 3, p. 869-884 16 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  6. Published

    Optimal scaling of the random walk Metropolis: general criteria for the 0.234 acceptance rule

    Sherlock, C., 03/2013, In: Journal of Applied Probability. 50, 1, p. 1-15 15 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  7. Published

    Optimal scaling of the random walk Metropolis on unimodal elliptically symmetric targets.

    Sherlock, C. & Roberts, G., 2009, In: Bernoulli. 15, 3, p. 774-798 25 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  8. Published

    Particle learning approach to Bayesian model selection: an application from neurology

    Taylor, S., Ridall, G., Sherlock, C. & Fearnhead, P., 2014, The contribution of young researchers to Bayesian statistics: Proceedings of BAYSM2013. Lanzarone, E. & Leva, F. (eds.). Springer, p. 165-167 3 p. (Springer Proceedings in Mathematics and Statistics; vol. 63).

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter

  9. Published

    Particle Metropolis-adjusted Langevin algorithms

    Nemeth, C., Sherlock, C. & Fearnhead, P., 09/2016, In: Biometrika. 103, 3, p. 701-717 17 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  10. Published

    Pseudo-marginal Metropolis-Hastings sampling using averages of unbiased estimators

    Sherlock, C. G., Thiery, A. & Lee, A., 09/2017, In: Biometrika. 104, 3, p. 727-734 8 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  11. Published

    Recruitment prediction for multicenter clinical trials based on a hierarchical Poisson–gamma model: Asymptotic analysis and improved intervals

    Mountain, R. & Sherlock, C., 30/06/2022, In: Biometrics. 78, 2, p. 636-648 13 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  12. Published

    Spatial and temporal patterns in antimicrobial resistance of Salmonella Typhimurium amongst cattle in England and Wales

    Cox, R., Su, T-L., Clough, H., Woodward, MJ. & Sherlock, C., 2012, In: Epidemiology and Infection. p. 1-12 12 p., PMID: 22214772.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  13. Published

    SwISS: A Scalable Markov chain Monte Carlo Divide-and-Conquer Strategy

    Vyner, C., Nemeth, C. & Sherlock, C., 8/08/2022.

    Research output: Working paper › Preprint

  14. Published

    SwISS: A Scalable Markov chain Monte Carlo Divide-and-Conquer Strategy

    Vyner, C., Nemeth, C. & Sherlock, C., 31/12/2023, In: Stat. 12, 1, 11 p., e523.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  15. Published

    Tamás P. Papp, Paul Fearnhead and Chris Sherlock's contribution to the discussion of “the Discussion Meeting on Probabilistic and statistical aspects of machine learning”

    Papp, T. P., Fearnhead, P. & Sherlock, C., 12/04/2024, In: Journal of the Royal Statistical Society: Series B (Statistical Methodology). 86, 2, p. 327-328 2 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  16. Published

    The Apogee to Apogee Path Sampler

    Sherlock, C., Urbas, S. & Ludkin, M., 2/10/2023, In: Journal of Computational and Graphical Statistics. 32, 4, p. 1436-1446 11 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  17. Published

    The prevalence of antimicrobial resistant Escherichia coli in sympatric wild rodents varies by season and host.

    Williams, N. J., Sherlock, C., Jones, T. R., Clough, H. E., Telfer, S. E., Begon, M., French, N. P. & Bennett, M., 2011, In: Journal of Applied Microbiology. 110, 4, p. 962-970 9 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  18. Published

    The random walk Metropolis : linking theory and practice through a case study.

    Sherlock, C., Fearnhead, P. & Roberts, G., 05/2010, In: Statistical Science. 25, 2, p. 172-190 19 p.

    Research output: Contribution to Journal/Magazine › Journal article

  19. Published

    Variance bounding of delayed-acceptance kernels

    Sherlock, C. & Lee, A., 30/09/2022, In: Methodology and Computing in Applied Probability. 24, 3, p. 2237-2260 24 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

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