11 citations · 22 across the 3 of their papers we have counts for
6 papers
Approximating the Likelihood in Approximate Bayesian Computation
Christopher C Drovandi, Clara Grazian, Kerrie Mengersen +1
This chapter will appear in the forthcoming Handbook of Approximate Bayesian Computation (2018). The conceptual and methodological framework that underpins approximate Bayesian com…
Jeffreys priors for mixture estimation: properties and alternatives
Clara Grazian, Christian P. Robert
While Jeffreys priors usually are well-defined for the parameters of mixtures of distributions, they are not available in closed form. Furthermore, they often are improper priors.…
Jeffreys priors for mixture estimation
Clara Grazian, Christian Robert
While Jeffreys priors usually are well-defined for the parameters of mixtures of distributions, they are not available in closed form. Furthermore, they often are improper priors.…
Accelerating Metropolis-Hastings algorithms by Delayed Acceptance
Marco Banterle, Clara Grazian, Anthony Lee +1
MCMC algorithms such as Metropolis-Hastings algorithms are slowed down by the computation of complex target distributions as exemplified by huge datasets. We offer in this paper a…
A discussion of "Bayesian model selection based on proper scoring rules" by A.P. Dawid and M. Musio
Clara Grazian, Ilaria Masiani, Christian P. Robert
This note is a discussion of the article "Bayesian model selection based on proper scoring rules" by A.P. Dawid and M. Musio, to appear in Bayesian Analysis. While appreciating the…
Accelerating Metropolis-Hastings algorithms: Delayed acceptance with prefetching
Marco Banterle, Clara Grazian, Christian P. Robert
MCMC algorithms such as Metropolis-Hastings algorithms are slowed down by the computation of complex target distributions as exemplified by huge datasets. We offer in this paper an…