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One of the most influential recent results in network analysis is that many natural networks exhibit a power-law or log-normal degree distribution. This has inspired numerous generative models that match this property. However, more recent…

Data Structures and Algorithms · Computer Science 2011-09-01 Isabelle Stanton , Ali Pinar

The configuration model was originally defined for undirected networks and has recently been extended to directed networks. Many empirical networks are however neither undirected nor completely directed, but instead usually partially…

Probability · Mathematics 2015-09-30 Kristoffer Spricer , Tom Britton

Given two distributions F and G on the nonnegative integers we propose an algorithm to construct in- and out-degree sequences from samples of i.i.d. observations from F and G, respectively, that with high probability will be graphical, that…

Probability · Mathematics 2012-07-12 Ningyuan Chen , Mariana Olvera-Cravioto

We study directed random graphs (random graphs whose edges are directed) as they evolve in discrete time by the addition of nodes and edges. For two distinct evolution strategies, one that forces the graph to a condition of near acyclicity…

Statistical Mechanics · Physics 2007-05-23 Valmir C. Barbosa , Raul Donangelo , Sergio R. Souza

We study connected graphs with a fixed degree sequence, in the sparse setting where the number of edges grows linearly in the number of vertices. Using the relation to the configuration model, we identify the number of such connected graphs…

Combinatorics · Mathematics 2026-05-11 Sasha Bell , Serte Donderwinkel , Remco van der Hofstad

Randomising networks using a naive `accept-all' edge-swap algorithm is generally biased. Building on recent results for nondirected graphs, we construct an ergodic detailed balance Markov chain with non-trivial acceptance probabilities for…

Quantitative Methods · Quantitative Biology 2011-12-21 E. S. Roberts , A. C. C. Coolen

Random graphs with a given degree sequence are often constructed using the configuration model, which yields a random multigraph. We may adjust this multigraph by a sequence of switchings, eventually yielding a simple graph. We show that,…

Probability · Mathematics 2019-02-01 Svante Janson

Assortativity coefficients are important metrics to analyze both directed and undirected networks. In general, it is not guaranteed that the fitted model will always agree with the assortativity coefficients in the given network, and the…

Computation · Statistics 2022-01-11 Tiandong Wang , Jun Yan , Yelie Yuan , Panpan Zhang

In the new field of financial systemic risk, the network of interbank counterparty relationships can be described as a directed random graph. In "cascade models" of systemic risk, this "skeleton" acts as the medium through which financial…

Probability · Mathematics 2015-12-11 T. R. Hurd

Random graphs are more and more used for modeling real world networks such as evolutionary networks of proteins. For this purpose we look at two different models and analyze how properties like connectedness and degree distributions are…

Probability · Mathematics 2019-02-05 Klemens Taglieber , Uta Freiberg

Recent work on the structure of social networks and the internet has focussed attention on graphs with distributions of vertex degree that are significantly different from the Poisson degree distributions that have been widely studied in…

Statistical Mechanics · Physics 2009-10-31 M. E. J. Newman , S. H. Strogatz , D. J. Watts

Directed networks are ubiquitous and are necessary to represent complex systems with asymmetric interactions---from food webs to the World Wide Web. Despite the importance of edge direction for detecting local and community structure, it…

Physics and Society · Physics 2010-11-09 Jacob G. Foster , David V. Foster , Peter Grassberger , Maya Paczuski

The interactions between the components of complex networks are often directed. Proper modeling of such systems frequently requires the construction of ensembles of digraphs with a given sequence of in- and out-degrees. As the number of…

Physics and Society · Physics 2015-05-30 H. Kim , C. I. Del Genio , K. E. Bassler , Z. Toroczkai

We study the problem of generating graphs with prescribed degree sequences for bipartite, directed, and undirected networks. We first propose a sequential method for bipartite graph generation and establish a necessary and sufficient…

Methodology · Statistics 2026-03-13 Tong Sun , Jianshu Hao , Michael C. Fu , Guangxin Jiang

Complex systems, ranging from soft materials to wireless communication, are often organised as random geometric networks in which nodes and edges evenly fill up the volume of some space. Studying such networks is difficult because they…

Probability · Mathematics 2022-07-19 Ivan Kryven , Rik Versendaal

Random networks are widely used to model complex networks and research their properties. In order to get a good approximation of complex networks encountered in various disciplines of science, the ability to tune various statistical…

Disordered Systems and Neural Networks · Physics 2009-11-13 Andreas Pusch , Sebastian Weber , Markus Porto

(a) We propose a ``static'' construction procedure for random networks with given correlations of the degrees of the nearest-neighbor vertices. This is an equilibrium graph, maximally random under the constraint that its degree-degree…

Statistical Mechanics · Physics 2007-05-23 S. N. Dorogovtsev , J. F. F. Mendes , A. N. Samukhin

Let $F$ be a probability distribution with support on the non-negative integers. Four methods for generating a simple undirected graph with (approximate) degree distribution $F$ are described and compared. Two methods are based on the so…

Probability · Mathematics 2015-09-30 Tom Britton , Maria Deijfen , Anders Martin-Löf

Online social networks are a dominant medium in everyday life to stay in contact with friends and to share information. In Twitter, users can connect with other users by following them, who in turn can follow back. In recent years,…

Social and Information Networks · Computer Science 2022-05-06 Christoph Schweimer , Christine Gfrerer , Florian Lugstein , David Pape , Jan A. Velimsky , Robert Elsässer , Bernhard C. Geiger

We study random graph models for directed acyclic graphs, an important class of networks that includes citation networks, food webs, and feed-forward neural networks among others. We propose two specific models, roughly analogous to the…

Physics and Society · Physics 2009-10-16 Brian Karrer , M. E. J. Newman
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