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arxiv: 2203.11817 · v1 · pith:XT444KDC · submitted 2022-03-14 · cs.SI · math.ST· stat.ME· stat.TH

Modeling Tie Duration in ERGM-Based Dynamic Network Models

Pavel N. Krivitsky (School of Mathematics , Statistics , University of New South Wales , Sydney , NSW , Australia) This is my paper

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classification cs.SI math.STstat.MEstat.TH
keywords durationframeworkmodelingdistributionsseparableachievableassumptionsdynamic
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Krivitsky and Handcock (2014) proposed a Separable Temporal ERGM (STERGM) framework for modeling social networks, which facilitates separable modeling of the tie duration distributions and the structural dynamics of tie formation. In this note, we explore the hazard structures achievable in this framework, with first- and higher-order Markov assumptions, and propose ways to model a variety of duration distributions in this framework.

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