Nial Friel

发表

Actor-Based Models for Longitudinal Networks

Alberto Caimo, Nial Friel, 2018, Encyclopedia of Social Network Analysis and Mining. 2nd Ed..

Bayesian Variational Inference for Exponential Random Graph Models

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

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..

Computationally efficient inference for latent position network models

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

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

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

Bayesian inference for exponential random graph models

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

Model-based clustering in networks with Stochastic Community Finding pdf

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

Introduction to “Efficient computational strategies for doubly intractable problems with applications to Bayesian social networks” by A. Caimo, A. Mira

Nial Friel, 2015, Stat. Comput..

Improving power posterior estimation of statistical evidence

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

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

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

Block clustering with collapsed latent block models

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

Optimal Bayesian estimators for latent variable cluster models

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

Noisy Hamiltonian Monte Carlo for Doubly Intractable Distributions

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

Calibration of conditional composite likelihood for Bayesian inference on Gibbs random fields

Nial Friel, Julien Stoehr, 2015, AISTATS.

Efficient Estimation of the number of neighbours in Probabilistic K Nearest Neighbour Classification pdf

Ji Won Yoon, Nial Friel, 2013, ArXiv.

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

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

Properties of latent variable network models

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

A generalized multiple-try version of the Reversible Jump algorithm

Francesco Bartolucci, Silvia Pandolfi, Nial Friel, 2014, Comput. Stat. Data Anal..

Bergm: Bayesian Exponential Random Graphs in R

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

Evidence and Bayes Factor Estimation for Gibbs Random Fields

Nial Friel, 2013 .

Proceedings of the 19th International Workshop on Statistical Modelling

Ernst Wit, Nial Friel, 2004 .

A new thresholding technique based on random sets

Nial Friel, Ilya S. Molchanov, 1999, Pattern Recognit..

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

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

A generalization of the Multiple-try Metropolis algorithm for Bayesian estimation and model selection

Francesco Bartolucci, Silvia Pandolfi, Nial Friel, 2010, AISTATS.

Bayesian inference for Gibbs random fields using composite likelihoods

Nial Friel, 2012, Proceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC).

Efficient model selection for probabilistic K nearest neighbour classification

Ji Won Yoon, Nial Friel, N. Friel, 2015, Neurocomputing.

Estimating the model evidence: a review

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

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

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

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.

Introduction to “Pre-processing for approximate Bayesian computation in image analysis” by M. Moores, C. Drovandi, K. Mengersen, C. Robert

Nial Friel, 2015, Stat. Comput..

Spatial hidden Markov models and species distributions

Nial Friel, Luigi Spezia, Alessandro Gimona, 2018 .

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

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

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

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

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

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

Bayesian Model Selection for Exponential Random Graph Models via Adjusted Pseudolikelihoods

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

Bayesian exponential random graph models with nodal random effects

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

Deterministic Bayesian inference for the p* model

Nial Friel, Haakon Austad, 2010, AISTATS.

Classification using distance nearest neighbours

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

Bayesian model selection for exponential random graph models

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

Estimating the evidence – a review

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

Actor-Based Models for Longitudinal Networks

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

Class of error metrics for gray-scale image comparison

Nial Friel, Ilya Molchanov, 1998, Optics & Photonics.

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.

Computational Statistics and Data Analysis

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

Adaptive Incremental Mixture Markov Chain Monte Carlo

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.

Tuning tempered transitions

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

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

Ioannis Ntzoufras, Nial Friel, Francesca Basini, 2021 .

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

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

Assessing epidemic curves for evidence of superspreading

Nial Friel, Joe Meagher, 2021 .

A Bayesian latent allocation model for clustering compositional data with application to the Great Barrier Reef

Kerrie Mengersen, Antonietta Mira, Nial Friel, 2021, 2105.02140.

Statistical Network Analysis with Bergm

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

Efficient calculation of the normalizing constant of the autologistic and related models on the cylinder and lattice

Anthony N. Pettitt, Nial Friel, A. Pettitt, 2003 .

Efficient bubbles for visual categorization tasks

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

A Bayesian Method for Motor Units Number Estimation (MUNE) Using Reversible Jump Markov Chain Monte Carlo (RJMCMC)

Nial Friel, Robert D. Henderson, Pamela A. McCombe, 2005 .

Bayesian Inference in Hidden Markov Random Fields for Binary Data Defined on Large Lattices

Anthony N. Pettitt, Ernst Wit, Nial Friel, 2009 .

Motor unit number estimation using reversible jump Markov chain Monte Carlo methods

Anthony N. Pettitt, Nial Friel, Robert D. Henderson, 2007 .

Actor-Based Models for Longitudinal Networks

Alberto Caimo, Nial Friel, Nial Friel, 2014 .

An adaptive MCMC method for multiple changepoint analysis with applications to large datasets

Nial Friel, N. Friel, Alan Benson, 2016, 1606.09419.

Likelihood Estimation and Inference for the Autologistic Model

Anthony N. Pettitt, Nial Friel, A. Pettitt, 2004 .

Recursive computing and simulation-free inference for general factorizable models

Håvard Rue, Nial Friel, H. Rue, 2007 .