4 papers
Functional Estimation of the Marginal Likelihood
Omiros Papaspiliopoulos, Timothée Stumpf-Fétizon, Jonathan Weare
We propose a framework for computing, optimizing and integrating with respect to a smooth marginal likelihood in statistical models that involve high-dimensional parameters/latent…
Exact Bayesian inference for Markov switching diffusions
Timothée Stumpf-Fétizon, Krzysztof ÅatuszyÅski, Jan Palczewski +1
We develop the first exact Bayesian methodology for the problem of inference in discretely observed regime switching diffusions. Switching diffusion models extend ordinary diffusio…
Scalable Bernoulli factories for Bayesian inference with intractable likelihoods
Timothée Stumpf-Fétizon, Flávio B. Gonçalves
Bernoulli factory MCMC algorithms implement accept-reject Markov chains without explicit computation of acceptance probabilities, and are used to target posterior distributions ass…
MCMC for multi-modal distributions
Krzysztof ÅatuszyÅski, Matthew T. Moores, Timothée Stumpf-Fétizon
We explain the fundamental challenges of sampling from multimodal distributions, particularly for high-dimensional problems. We present the major types of MCMC algorithms that are…