Jordan Franks

Handbook of Approximate Bayesian Computation.

Jordan Franks, 2020 .

Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo

Jouni Helske, Matti Vihola, Jordan Franks, 2016, Scandinavian Journal of Statistics.

Markov chain Monte Carlo importance samplers for Bayesian models with intractable likelihoods

Jordan Franks, Jordan Franks, 2019, 1904.05886.

On the use of ABC-MCMC with inflated tolerance and post-correction

Matti Vihola, Jordan Franks, 2019 .

On the use of approximate Bayesian computation Markov chain Monte Carlo with inflated tolerance and post-correction

Matti Vihola, Jordan Franks, M. Vihola, 2019 .

Unbiased Inference for Discretely Observed Hidden Markov Model Diffusions

Matti Vihola, Kody J. H. Law, Ajay Jasra, 2018, SIAM/ASA J. Uncertain. Quantification.

Importance sampling correction versus standard averages of reversible MCMCs in terms of the asymptotic variance

Matti Vihola, Jordan Franks, M. Vihola, 2017, 1706.09873.

Importance sampling and delayed acceptance via a Peskun type ordering

Matti Vihola, Jordan Franks, M. Vihola, 2017 .