1 citations · 2 across the 3 of their papers we have counts for
3 papers
stat.CO2019★ 1 cited
Likelihood-free approximate Gibbs sampling
G. S. Rodrigues, D. J. Nott, S. A. Sisson
Likelihood-free methods such as approximate Bayesian computation (ABC) have extended the reach of statistical inference to problems with computationally intractable likelihoods. Su…
stat.CO2017★ 1 cited
Recalibration: A post-processing method for approximate Bayesian computation
G. S. Rodrigues, D. Prangle, S. A. Sisson
A new recalibration post-processing method is presented to improve the quality of the posterior approximation when using Approximate Bayesian Computation (ABC) algorithms. Recalibr…
stat.CO2014
Functional regression approximate Bayesian computation for Gaussian process density estimation
G. S. Rodrigues, David J. Nott, S. A. Sisson
We propose a novel Bayesian nonparametric method for hierarchical modelling on a set of related density functions, where grouped data in the form of samples from each density funct…