9 citations · 23 across the 3 of their papers we have counts for
4 papers
Bootstrapped synthetic likelihood
Richard G. Everitt
Approximate Bayesian computation (ABC) and synthetic likelihood (SL) techniques have enabled the use of Bayesian inference for models that may be simulated, but for which the likel…
Marginal sequential Monte Carlo for doubly intractable models
Richard G. Everitt, Dennis Prangle, Philip Maybank +1
Bayesian inference for models that have an intractable partition function is known as a doubly intractable problem, where standard Monte Carlo methods are not applicable. The past…
Fast approximate Bayesian inference for stable differential equation models
Philip Maybank, Ingo Bojak, Richard G. Everitt
Inference for mechanistic models is challenging because of nonlinear interactions between model parameters and a lack of identifiability. Here we focus on a specific class of mecha…
An ABC interpretation of the multiple auxiliary variable method
Dennis Prangle, Richard G. Everitt
We show that the auxiliary variable method (Møller et al., 2006; Murray et al., 2006) for inference of Markov random fields can be viewed as an approximate Bayesian computation met…