45 citations · 150 across the 12 of their papers we have counts for
5 papers · 1 filter
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…
Convergence of hybrid slice sampling via spectral gap
Krzysztof Łatuszyński, Daniel Rudolf
It is known that the simple slice sampler has robust convergence properties, however the class of problems where it can be implemented is limited. In contrast, we consider hybrid s…
Variance bounding and geometric ergodicity of Markov chain Monte Carlo kernels for approximate Bayesian computation
Anthony Lee, Krzysztof Latuszynski
Approximate Bayesian computation has emerged as a standard computational tool when dealing with the increasingly common scenario of completely intractable likelihood functions in B…
Nonasymptotic bounds on the estimation error of MCMC algorithms
Krzysztof Łatuszyński, Błażej Miasojedow, Wojciech Niemiro
We address the problem of upper bounding the mean square error of MCMC estimators. Our analysis is nonasymptotic. We first establish a general result valid for essentially all ergo…