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The Journal of Mathematical Sociology Volume 42, 2018 - Issue 1
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Original Articles

A perfect sampling method for exponential family random graph models

Carter T. ButtsDepartments of Sociology, Statistics, and EECS and Institute for Mathematical Behavioral Sciences, University of California, Irvine, CA, USACorrespondence[email protected]
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Pages 17-36 | Received 11 Oct 2017, Accepted 23 Oct 2017, Published online: 14 Nov 2017

Citations (13)

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Read on this site (4)

Carter T. Butts. (2024) Continuous time graph processes with known ERGM equilibria: contextual review, extensions, and synthesis. The Journal of Mathematical Sociology 48:2, pages 129-171.
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Carter T. Butts. (2022) A dynamic process reference model for sparse networks with reciprocity. The Journal of Mathematical Sociology 46:1, pages 1-27.
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Andee Kaplan, Mark S. Kaiser, Soumendra N. Lahiri & Daniel J. Nordman. (2020) Simulating Markov Random Fields With a Conclique-Based Gibbs Sampler. Journal of Computational and Graphical Statistics 29:2, pages 286-296.
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Carter T. Butts. A return to biased nets: new specifications and approximate Bayesian Inference*. The Journal of Mathematical Sociology 0:0, pages 1-29.
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Articles from other publishers (9)

Moses Ahomka Yeboah. (2023) How do family and non-family ties affect knowledge sharing in SMEs in a developing country? Linking social capital and network strength. Management Research Review 46:10, pages 1427-1448.
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Xiwen Jiang, Selena Margarita Livas, Fan Yin, Sayantan Banerjee, Carter T. Butts & Weining Shen. (2023) Structure recovery and trend estimation for dynamic network analysis. Stat 12:1.
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Jaewoo Park, Ick Hoon Jin & Michael Schweinberger. (2022) Bayesian model selection for high-dimensional Ising models, with applications to educational data. Computational Statistics & Data Analysis 165, pages 107325.
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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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Yue Yu, Gianmarc Grazioli, Megha H. Unhelkar, Rachel W. Martin & Carter T. Butts. (2020) Network Hamiltonian models reveal pathways to amyloid fibril formation. Scientific Reports 10:1.
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Caitlin Gray, Lewis Mitchell & Matthew Roughan. (2020) Bayesian Inference of Network Structure From Information Cascades. IEEE Transactions on Signal and Information Processing over Networks 6, pages 371-381.
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Andressa Cerqueira, Aurélien Garivier & Florencia Leonardi. (2020) A note on perfect simulation for Exponential Random Graph Models. ESAIM: Probability and Statistics 24, pages 138-147.
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Matthew T. Moores, Anthony N. Pettitt & Kerrie L. Mengersen. 2020. Case Studies in Applied Bayesian Data Science. Case Studies in Applied Bayesian Data Science 137 151 .
Johan Koskinen, Chiara Broccatelli, Peng Wang & Garry Robins. 2019. New Statistical Developments in Data Science. New Statistical Developments in Data Science 105 117 .

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