Unbiased inference for discretely observed hidden Markov model diffusions NK Chada, J Franks, A Jasra, KJH Law, M Vihola
arXiv preprint arXiv:1807.10259, 2018
35 2018 Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo M Vihola, J Helske, J Franks
Scandinavian Journal of Statistics 47 (4), 1339-1376, 2020
34 2020 On the use of approximate Bayesian computation Markov chain Monte Carlo with inflated tolerance and post-correction M Vihola, J Franks
Biometrika 107 (2), 381-395, 2020
17 2020 Importance sampling correction versus standard averages of reversible MCMCs in terms of the asymptotic variance J Franks, M Vihola
Stochastic Processes and their Applications 130 (10), 6157-6183, 2020
14 2020 Importance sampling type correction of Markov chain Monte Carlo and exact approximations M Vihola, J Helske, J Franks
Preprint 1609, v2, 2016
11 2016 Importance sampling and delayed acceptance via a Peskun type ordering J Franks, M Vihola
Preprint, 2020
3 2020 Handbook of Approximate Bayesian Computation. JJ Franks
Journal of the American Statistical Association 115 (532), 2100-2101, 2020
2 2020 On J Franks, A Valette
Annales mathématiques Blaise Pascal 21 (1), 61-69, 2014
1 2014 Markov chain Monte Carlo importance samplers for Bayesian models with intractable likelihoods J Franks
arXiv preprint arXiv:1904.05886, 2019
2019 Article [C] J Franks, A Jasra, KJH Law, M Vihola
Markov Chain Monte Carlo Importance Samplers for Bayesian Models with …, 2019
2019 Article [A] M Vihola, J Helske, J Franks
Markov Chain Monte Carlo Importance Samplers for Bayesian Models with …, 2019
2019 ANNALES MATHÉMATIQUES A Banerjee
Annales mathématiques Blaise Pascal 21, 1-23, 2014
2014 Accelerating MCMC with an approximation J Helske, M Vihola, J Franks
Matti ViholaDepartment of Mathematics and Statistics, University of JyväskyläVahvistettu sähköpostiosoite verkkotunnuksessa jyu.fi
