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Random graphs with a given degree sequence are a useful model capturing several features absent in the classical Erd˝ os-Rényi model, such as dependent edges and non-binomial degrees. In this paper, we use a characterization due to Erd˝ os and Gallai to develop a sequential algorithm for generating a random labeled graph with a given degree sequence. The… (More)

In order to conduct analyses of networked systems where connections between individuals take on a range of values – counts, continuous strengths or ordinal rankings – a common technique is to dichotomize the data according to their positions with respect to a threshold value. However, there are two issues to consider: how the results of the analysis depend… (More)

Various methods have been proposed for creating a binary version of a complex network with valued ties. Rather than the default method of choosing a single threshold value about which to dichotomize, we consider a method of choosing the highest k outbound arcs from each person and assigning a binary tie, as this has the advantage of minimizing the isolation… (More)

We present a unified approach to modelling dyadic relational data, namely that seen in social, biological and technological networks, without restriction to the binary format. The approach involves three principles: considering the marginal specification of any edge as the fundamental unit, embedding as much dependence as possible in latent structural… (More)

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