43 citations · 242 across the 46 of their papers we have counts for
6 papers · 1 filter
Improving power posterior estimation of statistical evidence
Nial Friel, Merrilee Hurn, Jason Wyse
The statistical evidence (or marginal likelihood) is a key quantity in Bayesian statistics, allowing one to assess the probability of the data given the model under investigation.…
Bayesian inference for Gibbs random fields using composite likelihoods
Nial Friel
Gibbs random fields play an important role in statistics, for example the autologistic model is commonly used to model the spatial distribution of binary variables defined on a lat…
Model-based clustering in networks with Stochastic Community Finding
Aaron F. McDaid, Brendan Thomas Murphy, Nial Friel +1
In the model-based clustering of networks, blockmodelling may be used to identify roles in the network. We identify a special case of the Stochastic Block Model (SBM) where we cons…
Clustering in networks with the collapsed Stochastic Block Model
Aaron F. McDaid, Thomas Brendan Murphy, Nial Friel +1
An efficient MCMC algorithm is presented to cluster the nodes of a network such that nodes with similar role in the network are clustered together. This is known as block-modelling…
Bergm: Bayesian Exponential Random Graphs in R
Alberto Caimo, Nial Friel
In this paper we describe the main featuress of the Bergm package for the open-source R software which provides a comprehensive framework for Bayesian analysis for exponential rand…
Bayesian model selection for exponential random graph models
Alberto Caimo, Nial Friel
Exponential random graph models are a class of widely used exponential family models for social networks. The topological structure of an observed network is modelled by the relati…