35 citations · 95 across the 23 of their papers we have counts for
5 papers · 1 filter
Distributed Computation for Marginal Likelihood based Model Choice
Alexander Buchholz, Daniel Ahfock, Sylvia Richardson
We propose a general method for distributed Bayesian model choice, using the marginal likelihood, where a data set is split in non-overlapping subsets. These subsets are only acces…
MCMC algorithms for Bayesian variable selection in the logistic regression model for large-scale genomic applications
Manuela Zucknick, Sylvia Richardson
In large-scale genomic applications vast numbers of molecular features are scanned in order to find a small number of candidates which are linked to a particular disease or phenoty…
Sampling from Dirichlet process mixture models with unknown concentration parameter: Mixing issues in large data implementations
David I. Hastie, Silvia Liverani, Sylvia Richardson
We consider the question of Markov chain Monte Carlo sampling from a general stick-breaking Dirichlet process mixture model, with concentration parameter alpha. This paper introduc…
PReMiuM: An R Package for Profile Regression Mixture Models using Dirichlet Processes
Silvia Liverani, David I. Hastie, Lamiae Azizi +2
PReMiuM is a recently developed R package for Bayesian clustering using a Dirichlet process mixture model. This model is an alternative to regression models, non-parametrically lin…
Evolutionary Stochastic Search for Bayesian model exploration
Leonardo Bottolo, Sylvia Richardson
Implementing Bayesian variable selection for linear Gaussian regression models for analysing high dimensional data sets is of current interest in many fields. In order to make such…