DERGMs: Degeneracy-restricted exponential family random graph models.
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- Network Science, 2022, v. 10, n. 1, p. 82, doi. 10.1017/nws.2022.5
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Works matching IS 20501242 AND DT 2022 AND VI 10 AND IP 1
Results: 7
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A theoretical and empirical comparison of the temporal exponential random graph model and the stochastic actor-orientedmodel - Corrigendum.
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- Network Science, 2022, v. 10, n. 1, p. 111, doi. 10.1017/nws.2022.11
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3
Role detection in bicycle-sharing networks using multilayer stochastic block models.
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- Network Science, 2022, v. 10, n. 1, p. 46, doi. 10.1017/nws.2021.21
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4
Faster MCMC for Gaussian latent position networkmodels.
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- Network Science, 2022, v. 10, n. 1, p. 20, doi. 10.1017/nws.2022.1
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5
The stochastic actor-orientedmodel is a theory asmuch as it is amethod and must be subject to theory tests.
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- Network Science, 2022, v. 10, n. 1, p. 15, doi. 10.1017/nws.2022.7
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6
Circular specifications and "predicting" with information from the future: Errors in the empirical SAOM-TERGM comparison of Leifeld & Cranmer.
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- Network Science, 2022, v. 10, n. 1, p. 3, doi. 10.1017/nws.2022.6
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7
Editors' Note.
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- Network Science, 2022, v. 10, n. 1, p. 1, doi. 10.1017/nws.2022.8
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