290 citations · 319 across the 4 of their papers we have counts for
5 papers
On the marginal likelihood and cross-validation
Edwin Fong, Chris Holmes
In Bayesian statistics, the marginal likelihood, also known as the evidence, is used to evaluate model fit as it quantifies the joint probability of the data under the prior. In co…
General Bayesian Updating and the Loss-Likelihood Bootstrap
Simon Lyddon, Chris Holmes, Stephen Walker
In this paper we revisit the weighted likelihood bootstrap, a method that generates samples from an approximate Bayesian posterior of a parametric model. We show that the same meth…
Assigning a value to a power likelihood in a general Bayesian model
Chris Holmes, Stephen Walker
Bayesian approaches to data analysis and machine learning are widespread and popular as they provide intuitive yet rigorous axioms for learning from data; see Bernardo and Smith (2…
Characterising variation of nonparametric random probability measures using the Kullback-Leibler divergence
James Watson, Luis Nieto-Barajas, Chris Holmes
This work studies the variation in Kullback-Leibler divergence between random draws from some popular nonparametric processes and their baseline measure. In particular we focus on…
A General Framework for Updating Belief Distributions
Pier Giovanni Bissiri, Chris Holmes, Stephen Walker
We propose a framework for general Bayesian inference. We argue that a valid update of a prior belief distribution to a posterior can be made for parameters which are connected to…