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Research

Results for Markov jump process

Publications & Outputs

  1. Accelerating inference for stochastic kinetic models

    Lowe, T. E., Golightly, A. & Sherlock, C., 30/09/2023, In: Computational Statistics and Data Analysis. 185, 21 p., 107760.

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

  2. Direct statistical inference for finite Markov jump processes via the matrix exponential

    Sherlock, C., 31/12/2021, In: Computational Statistics. 36, 4, p. 2863-2887 25 p.

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

  3. Efficient sampling of conditioned Markov jump processes

    Golightly, A. & Sherlock, C. G., 13/02/2019, (E-pub ahead of print) In: Statistics and Computing. 15 p.

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

  4. Optimal scaling of the independence sampler: theory and practice

    Lee, C. & Neal, P. J., 2/02/2018, In: Bernoulli. 24, 3, p. 1636-1652 17 p.

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

  5. Efficient particle MCMC for exact inference in stochastic biochemical network models through approximation of expensive likelihoods

    Golightly, A., Henderson, D. & Sherlock, C., 09/2015, In: Statistics and Computing. 25, 5, p. 1039-1055 17 p.

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

  6. Convergence of Markov processes near saddle fixed points.

    Turner, A. G., 1/03/2007, In: Annals of Probability. 35, 3, p. 1141-1171 31 p.

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