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Journal of Computational and Graphical Statistics Volume 28, 2019 - Issue 1
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High-Dimensional and Multivariate Methods

Multiresolution Network Models

Bailey K. FosdickDepartment of Statistics, Colorado State University, Fort Collins, COORCID Iconhttp://orcid.org/0000-0003-3736-2219
ORCID Icon,
Tyler H. McCormickDepartment of Statistics, Department of Sociology, University of Washington, Seattle, WAORCID Iconhttp://orcid.org/0000-0002-6490-1129
ORCID Icon,
Thomas Brendan MurphySchool of Mathematics and Statistics, University College Dublin, Belfield, Dublin, Ireland
,
Tin Lok James NgSchool of Mathematics and Statistics, University College Dublin, Belfield, Dublin, Ireland
&
Ted WestlingDepartment of Statistics, University of Washington, Seattle, WAORCID Iconhttp://orcid.org/0000-0002-3362-1378
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Pages 185-196 | Received 01 Nov 2016, Published online: 05 Nov 2018

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Çağlar Hızlı & Serap Kırbız. (2022) A Bayesian Allocation Model Based Approach to Mixed Membership Stochastic Blockmodels. Applied Artificial Intelligence 36:1.
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Andrew J. Holbrook, Philippe Lemey, Guy Baele, Simon Dellicour, Dirk Brockmann, Andrew Rambaut & Marc A. Suchard. (2021) Massive Parallelization Boosts Big Bayesian Multidimensional Scaling. Journal of Computational and Graphical Statistics 30:1, pages 11-24.
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Articles from other publishers (10)

Riccardo Rastelli & Marco Corneli. (2023) Continuous latent position models for instantaneous interactions. Network Science, pages 1-29.
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Silvia D’Angelo, Marco Alfò & Michael Fop. (2023) Model-based clustering for multidimensional social networks. Journal of the Royal Statistical Society Series A: Statistics in Society 186:3, pages 481-507.
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Kathryn Turnbull, Christopher Nemeth, Matthew Nunes & Tyler McCormick. (2023) Sequential estimation of temporally evolving latent space network models. Computational Statistics & Data Analysis 179, pages 107627.
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Xian Yao Gwee, Isobel Claire Gormley & Michael Fop. (2023) A Latent Shrinkage Position Model for Binary and Count Network Data. Bayesian Analysis -1:-1.
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Sirio Legramanti, Tommaso Rigon, Daniele Durante & David B. Dunson. (2022) Extended stochastic block models with application to criminal networks. The Annals of Applied Statistics 16:4.
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Izabel Nolau & Gustavo S. Ferreira. (2022) An alternative class of models to position social network groups in latent spaces. Brazilian Journal of Probability and Statistics 36:2.
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Tin Lok James Ng, Thomas Brendan Murphy, Ted Westling, Tyler H. McCormick & Bailey Fosdick. (2021) Modeling the social media relationships of Irish politicians using a generalized latent space stochastic blockmodel. The Annals of Applied Statistics 15:4.
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Michael Schweinberger, Pavel N. Krivitsky, Carter T. Butts & Jonathan R. Stewart. (2020) Exponential-Family Models of Random Graphs: Inference in Finite, Super and Infinite Population Scenarios. Statistical Science 35:4.
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Beau Dabbs, Samrachana Adhikari & Tracy Sweet. (2020) Conditionally Independent Dyads (CID) network models: A latent variable approach to statistical social network analysis. Social Networks 63, pages 122-133.
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Emily BrezaArun G. ChandrasekharTyler H. McCormickMengjie Pan. (2020) Using Aggregated Relational Data to Feasibly Identify Network Structure without Network Data. American Economic Review 110:8, pages 2454-2484.
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