N. Friel

Adrian E. Raftery, Nial Friel, Florian Maire, 2016, Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America.

Improving power posterior estimation of statistical evidence

Nial Friel, Merrilee Hurn, Jason Wyse, 2012, Stat. Comput..

Estimating the evidence – a review

Nial Friel, Jason Wyse, N. Friel, 2011, 1111.1957.

Optimal Bayesian estimators for latent variable cluster models

Nial Friel, Riccardo Rastelli, N. Friel, 2016, Statistics and Computing.

Assessing epidemic curves for evidence of superspreading

N. Friel, J. Meagher, 2021, Journal of the Royal Statistical Society. Series A,.

Noisy Monte Carlo: convergence of Markov chains with approximate transition kernels

Pierre Alquier, Richard G. Everitt, Nial Friel, 2014, Statistics and Computing.

Investigation of the widely applicable Bayesian information criterion

J. P. McKeone, C. J. Oates, A. N. Pettitt, 2015, Stat. Comput..

Computational Statistics and Data Analysis

Neil J. Hurley, Thomas Brendan Murphy, Aaron F. McDaid, 2022 .

Model-based clustering in networks with Stochastic Community Finding pdf

Neil J. Hurley, Thomas Brendan Murphy, Aaron F. McDaid, 2012, ArXiv.

Interlocking directorates in Irish companies using a latent space model for bipartite networks

Adrian E Raftery, Nial Friel, Riccardo Rastelli, 2016, Proceedings of the National Academy of Sciences.

Bayesian Variational Inference for Exponential Random Graph Models

Nial Friel, Linda S. L. Tan, N. Friel, 2018, Journal of Computational and Graphical Statistics.

Bayesian exponential random graph models with nodal random effects

Alberto Caimo, Nial Friel, Göran Kauermann, 2014, Soc. Networks.

Bayesian inference for exponential random graph models

Alberto Caimo, Nial Friel, N. Friel, 2010, Soc. Networks.

Choosing the number of groups in a latent stochastic blockmodel for dynamic networks

Nial Friel, Riccardo Rastelli, Pierre Latouche, 2017, Network Science.

Informed sub-sampling MCMC: approximate Bayesian inference for large datasets

Pierre Alquier, Nial Friel, Florian Maire, 2017, Stat. Comput..

Light and Widely Applicable MCMC: Approximate Bayesian Inference for Large Datasets

Pierre Alquier, N. Friel, F. Maire, 2015, 1503.04178.

Block clustering with collapsed latent block models

Nial Friel, Jason Wyse, N. Friel, 2010, Statistics and Computing.

Mortality Projections using Generalized Additive Models with applications to annuity values for the Irish population

N. Friel, M. Hall, 2010, Annals of Actuarial Science.

Exploiting Multi-Core Architectures for Reduced-Variance Estimation with Intractable Likelihoods

Antonietta Mira, Nial Friel, Chris. J. Oates, 2014, 1408.4663.

Recursive computing for Markov random fields

H. Rue, N. Friel, 2005 .

Choosing the number of clusters in a finite mixture model using an exact integrated completed likelihood criterion

N. Friel, Riccardo Rastelli, M. Bertoletti, 2015, Metron.

Choosing the number of clusters in a finite mixture model using an exact integrated completed likelihood criterion

Nial Friel, Riccardo Rastelli, Marco Bertoletti, 2014, METRON.

Inferring structure in bipartite networks using the latent blockmodel and exact ICL

Nial Friel, Pierre Latouche, Jason Wyse, 2014, Network Science.

Noisy Hamiltonian Monte Carlo for Doubly Intractable Distributions

Alan Benson, Nial Friel, Julien Stoehr, 2017, Journal of Computational and Graphical Statistics.

Assessing competitive balance in the English Premier League for over forty seasons using a stochastic block model

N. Friel, I. Ntzoufras, Francesca Basini, 2021, Journal of the Royal Statistical Society Series A: Statistics in Society.

Properties of latent variable network models

Adrian E. Raftery, Nial Friel, Riccardo Rastelli, 2015, Network Science.

Multivariate Conway-Maxwell-Poisson Distribution: Sarmanov Method and Doubly Intractable Bayesian Inference

Hernando Ombao, Nial Friel, Wagner Barreto-Souza, 2021, J. Comput. Graph. Stat..

Spatial hidden Markov models and species distributions

Nial Friel, Luigi Spezia, Alessandro Gimona, 2018 .

Latent Position Network Models

A. Raftery, N. Friel, Riccardo Rastelli, 2023, 2304.02979.

Computationally efficient inference for latent position network models

Nial Friel, Florian Maire, Riccardo Rastelli, 2018, 1804.02274.

Bayesian model selection for the latent position cluster model for social networks

Nial Friel, Jason Wyse, Caitríona Ryan, 2013, Network Science.

Calibrating COVID-19 susceptible-exposed-infected-removed models with time-varying effective contact rates

David J. P. O'Sullivan, Joseph D. O’Brien, N. Friel, 2021, Philosophical Transactions of the Royal Society A.

Approximate simulation-free Bayesian inference for multiple changepoint models with dependence within segments

Haavard Rue, Nial Friel, Jason Wyse, 2010, 1011.5038.

Actor-Based Models for Longitudinal Networks

Alberto Caimo, Nial Friel, N. Friel, 2014, Encyclopedia of Social Network Analysis and Mining.

Bayesian testing of scientific expectations under exponential random graph models

P. Leifeld, N. Friel, J. Mulder, 2023, Soc. Networks.

Statistical Network Analysis with Bergm

Alberto Caimo, Nial Friel, Lampros Bouranis, 2021, J. Stat. Softw..

Model comparison for Gibbs random fields using noisy reversible jump Markov chain Monte Carlo

Nial Friel, Lampros Bouranis, Florian Maire, 2017, Comput. Stat. Data Anal..

Bayesian Model Selection for Exponential Random Graph Models via Adjusted Pseudolikelihoods

Nial Friel, Lampros Bouranis, Florian Maire, 2017, Journal of Computational and Graphical Statistics.

Efficient Bayesian inference for exponential random graph models by correcting the pseudo-posterior distribution

Nial Friel, Lampros Bouranis, Florian Maire, 2015, Soc. Networks.

Bergm: Bayesian Exponential Random Graphs in R

Alberto Caimo, Nial Friel, N. Friel, 2012, 1201.2770.

Bayesian model selection for exponential random graph models

Alberto Caimo, Nial Friel, N. Friel, 2012, Soc. Networks.

Evaluating squat performance with a single inertial measurement unit

Brian Caulfield, Martin O'Reilly, Darragh Whelan, 2015, 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN).

Estimating the model evidence: a review

Nial Friel, Jason Wyse, N. Friel, 2011 .

Tuning tempered transitions

Nial Friel, Merrilee Hurn, Gundula Behrens, 2010, Stat. Comput..

Classification using distance nearest neighbours

Anthony N. Pettitt, Nial Friel, A. Pettitt, 2010, Stat. Comput..

Sequencing and analysis of an Irish human genome

N. Friel, S. Cronin, O. Hardiman, 2010 .

collpcm: Bayesian model selection in latent position cluster models for networks

N. Friel, J. Wyse, Caitriona M. Ryan, 2021 .

Efficient bubbles for visual categorization tasks

Philippe G. Schyns, Nial Friel, P. Schyns, 2011, Vision Research.