Items where Author is "Sherlock, Chris"

Journal Article

Luo, Yu and Sherlock, Chris (2025) Bayesian inference for the Markov-modulated Poisson process with an outcome process. Journal of the Royal Statistical Society: Series C (Applied Statistics). ISSN 0035-9254 (In Press)

Papp, Tamas and Sherlock, Chris (2024) Scalable couplings for the random walk Metropolis algorithm. Journal of the Royal Statistical Society: Series B (Statistical Methodology). ISSN 1369-7412 (In Press)

Papp, Tamás P and Fearnhead, Paul and Sherlock, Chris (2024) 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”. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 86 (2). pp. 327-328. ISSN 1369-7412

Vyner, Callum and Nemeth, Christopher and Sherlock, Chris (2023) SwISS : A Scalable Markov chain Monte Carlo Divide-and-Conquer Strategy. Stat, 12 (1): e523. ISSN 2049-1573

Sherlock, Chris and Urbas, Szymon and Ludkin, Matthew (2023) The Apogee to Apogee Path Sampler. Journal of Computational and Graphical Statistics, 32 (4). pp. 1436-1446. ISSN 1061-8600

Lowe, Tom E. and Golightly, Andrew and Sherlock, Chris (2023) Accelerating inference for stochastic kinetic models. Computational Statistics and Data Analysis, 185: 107760. ISSN 0167-9473

Ludkin, Matthew and Sherlock, Chris (2023) Hug and Hop : a discrete-time, nonreversible Markov chain Monte Carlo algorithm. Biometrika, 110 (2). pp. 301-318. ISSN 0006-3444

Sherlock, Chris and Golightly, Andrew (2023) Exact Bayesian inference for discretely observed Markov Jump Processes using finite rate matrices. Journal of Computational and Graphical Statistics, 32 (1). pp. 36-48. ISSN 1061-8600

Sherlock, Chris and Lee, Anthony (2022) Variance bounding of delayed-acceptance kernels. Methodology and Computing in Applied Probability, 24 (3). pp. 2237-2260. ISSN 1387-5841

Mountain, Rachael and Sherlock, Chris (2022) Recruitment prediction for multicenter clinical trials based on a hierarchical Poisson–gamma model : Asymptotic analysis and improved intervals. Biometrics, 78 (2). pp. 636-648. ISSN 0006-341X

Sherlock, Chris and Thiery, Alexandre (2022) A discrete bouncy particle sampler. Biometrika, 109 (2). pp. 335-349. ISSN 0006-3444

Golightly, Andrew and Sherlock, Chris (2022) Augmented pseudo-marginal Metropolis-Hastings for partially observed diffusion processes. Statistics and Computing, 32: 21. ISSN 0960-3174

Sherlock, Chris (2021) Direct statistical inference for finite Markov jump processes via the matrix exponential. Computational Statistics, 36 (4). pp. 2863-2887. ISSN 0943-4062

Sherlock, Chris and Thiery, Alexandre and Golightly, Andrew (2021) Efficiency of delayed-acceptance random walk Metropolis algorithms. Annals of Statistics, 49 (5). pp. 2972-2990. ISSN 0090-5364

Taylor, Simon and Sherlock, Chris and Ridall, Gareth and Fearnhead, Paul (2020) Motor unit number estimation via sequential Monte Carlo. Computational Statistics and Data Analysis, 144: 106845. ISSN 0167-9473

Sherlock, Chris and Fearnhead, Paul and Roberts, Gareth (2010) The random walk Metropolis : linking theory and practice through a case study. Statistical Science, 25 (2). pp. 172-190. ISSN 0883-4237

Sherlock, Chris and Roberts, Gareth (2009) Optimal scaling of the random walk Metropolis on unimodal elliptically symmetric targets. Bernoulli, 15 (3). pp. 774-798. ISSN 1350-7265

Monograph

Vyner, Callum and Nemeth, Christopher and Sherlock, Chris (2022) SwISS : A Scalable Markov chain Monte Carlo Divide-and-Conquer Strategy. Other. UNSPECIFIED.

Thesis

Vyner, Callum and Sherlock, Chris and Nemeth, Christopher (2023) Contributions to Divide-and-Conquer MCMC. PhD thesis, Lancaster University.

Urbas, Szymon and Sherlock, Chris (2022) Bayesian inference and prediction for the inhomogeneous Poisson process, and a robust competitor to Hamiltonian Monte Carlo. PhD thesis, Lancaster University.

Malory, Sean and Sherlock, Chris (2021) Bayesian inference for stochastic processes. PhD thesis, Lancaster University.

Barlow, Anna and Sherlock, Chris and Tawn, Jonathan (2021) Flood Events : Extreme Value Problems and Efficient Estimation of Loss. PhD thesis, Lancaster University.

Yates, Katie and Pavlidis, Nicos and Sherlock, Chris (2018) Low-Density Cluster Separators for Large, High-Dimensional, Mixed and Non-Linearly Separable Data. PhD thesis, Lancaster University.

Weldon, Matthew Philip and Titman, Andrew and Sherlock, Chris (2017) School choice, competition and ethnic segregation in Lancashire : evidence from structural models of two-sided matching. PhD thesis, Lancaster University.

Lampaki, Ioanna and Sherlock, Chris (2016) Markov chain Monte Carlo methodoloy for inference with generalised linear spatial models. PhD thesis, Lancaster University.

Patel, Shreena and Sherlock, Chris (2016) Understanding consumer demand in customised pricing environments. PhD thesis, Lancaster University.

Giagos, Vasileios and Fearnhead, Paul and Sherlock, Chris and Wit, Ernst (2010) Inference for auto-regulatory genetic networks using diffusion process approximations. PhD thesis, Lancaster University.

Sherlock, Chris (2006) Methodology for inference on the Markov modulated Poisson process and theory for optimal scaling of the random walk Metropolis. PhD thesis, Lancaster University.