Zobrazeno 1 - 10
of 66
pro vyhledávání: '"Nial Friel"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract The relative abundance of groups of species is often used in ecological surveys to estimate community composition, a metric that reflects patterns of commonness and rarity of biological assemblages. The focus of this paper is measurements of
Externí odkaz:
https://doaj.org/article/461a6e8929a84e729dc7bb4a804dd886
Publikováno v:
Journal of Statistical Software, Vol 104, Pp 1-23 (2022)
Recent advances in computational methods for intractable models have made network data increasingly amenable to statistical analysis. Exponential random graph models (ERGMs) emerged as one of the main families of models capable of capturing the compl
Externí odkaz:
https://doaj.org/article/9423e8e5545d484195811562a3f01882
Autor:
Alberto Caimo, Nial Friel
Publikováno v:
Journal of Statistical Software, Vol 61, Iss 1, Pp 1-25 (2014)
In this paper we describe the main features of the Bergm package for the open-source R software which provides a comprehensive framework for Bayesian analysis of exponential random graph models: tools for parameter estimation, model selection and goo
Externí odkaz:
https://doaj.org/article/9226936951014eb39872594d513dfa1a
Publikováno v:
Journal of Computational and Graphical Statistics. 32:483-500
In this article, a multivariate count distribution with Conway-Maxwell (COM)-Poisson marginals is proposed. To do this, we develop a modification of the Sarmanov method for constructing multivariate distributions. Our multivariate COM-Poisson (MultCO
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::746bb4ff1908b24b6da7893a97ce3cfc
https://doi.org/10.1080/10618600.2022.2116443
https://doi.org/10.1080/10618600.2022.2116443
Autor:
Joseph D. O'Brien, David O'Sullivan, Nial Friel, Thomas Brendan Murphy, James P. Gleeson, Norma Bargary
Publikováno v:
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
We describe the population-based susceptible-exposed-infected-removed (SEIR) model developed by the Irish Epidemiological Modelling Advisory Group (IEMAG), which advises the Irish government on COVID-19 responses. The model assumes a time-varying eff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1fad8b983deb455a61cfdf7e8fdc3ea
https://doi.org/10.1098/rsta.2021.0120
https://doi.org/10.1098/rsta.2021.0120
Competitive balance is a desirable feature in any professional sports league and encapsulates the notion that there is unpredictability in the outcome of games as opposed to an imbalanced league in which the outcome of some games are more predictable
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::445b9e92fbf7a2ecda6b15ed8faa673c
http://arxiv.org/abs/2107.08732
http://arxiv.org/abs/2107.08732
Autor:
Nial Friel, Linda S. L. Tan
Deriving Bayesian inference for exponential random graph models (ERGMs) is a challenging "doubly intractable" problem as the normalizing constants of the likelihood and posterior density are both intractable. Markov chain Monte Carlo (MCMC) methods w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68a5d52e7c53bdaae2f2d494a2414782
Publikováno v:
Network Science
Network Science, Cambridge Journals, 2018, 6, pp.469-493
Network Science, Cambridge Journals, 2018, 6, pp.469-493
Latent stochastic block models are flexible statistical models that are widely used in social network analysis. In recent years, efforts have been made to extend these models to temporal dynamic networks, whereby the connections between nodes are obs
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cdb5c99aae43d6744b9a98b8da5e221e
https://doi.org/10.1017/nws.2018.19
https://doi.org/10.1017/nws.2018.19
Publikováno v:
Network Science. 5:70-91
The latent position cluster model is a popular model for the statistical analysis of network data. This model assumes that there is an underlying latent space in which the actors follow a finite mixture distribution. Moreover, actors which are close
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eaa558c45af97e784612fcda84fd29c7
https://doi.org/10.1017/nws.2017.6
https://doi.org/10.1017/nws.2017.6
Publikováno v:
Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America
We propose adaptive incremental mixture Markov chain Monte Carlo (AIMM), a novel approach to sample from challenging probability distributions defined on a general state-space. While adaptive MCMC methods usually update a parametric proposal kernel w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0cb9a3b7f1bd5d1a5d56f1da31368613