1 citations · 3 across the 4 of their papers we have counts for
5 papers
Stereographic Markov Chain Monte Carlo
Jun Yang, Krzysztof Łatuszyński, Gareth O. Roberts
High-dimensional distributions, especially those with heavy tails, are notoriously difficult for off-the-shelf MCMC samplers: the combination of unbounded state spaces, diminishing…
Optimal Scaling of MCMC Beyond Metropolis
Sanket Agrawal, Dootika Vats, Krzysztof Łatuszyński +1
The problem of optimally scaling the proposal distribution in a Markov chain Monte Carlo algorithm is critical to the quality of the generated samples. Much work has gone into obta…
Exact Bayesian inference for diffusion driven Cox processes
Flavio B. Gonçalves, Krzysztof G. Łatuszyński, Gareth O. Roberts
In this paper, we present a novel methodology to perform Bayesian inference for Cox processes in which the intensity function is driven by a diffusion process. The novelty lies in…
Exact Monte Carlo likelihood-based inference for jump-diffusion processes
Flávio B. Gonçalves, Krzysztof G. Łatuszyński, Gareth O. Roberts
Statistical inference for discretely observed jump-diffusion processes is a complex problem which motivates new methodological challenges. Thus existing approaches invariably resor…
CLTs and asymptotic variance of time-sampled Markov chains
Krzysztof Latuszynski, Gareth O. Roberts
For a Markov transition kernel and a probability distribution on nonnegative integers, a time-sampled Markov chain evolves according to the transition kernel $P_μ = \sum_k…