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Asymptotic properties of random graph sequences, like occurrence of a giant component or full connectivity in Erd\H{o}s-R\'enyi graphs, are usually derived with very specific choices for defining parameters. The question arises to which…

Probability · Mathematics 2024-02-20 B. J. K. Kleijn , S. Rizzelli

In several scale free graph models the asymptotic degree distribution and the characteristic exponent change when only a smaller set of vertices is considered. Looking at the common properties of these models, we present sufficient…

Probability · Mathematics 2010-07-27 Agnes Backhausz , Tamas F. Mori

We propose a simple random process inducing various types of random graphs and the scale free random graphs among others. The model is of a threshold nature and differs from the preferential attachment approach discussed in the literature…

Disordered Systems and Neural Networks · Physics 2007-05-23 D. Volchenkov , Ph. Blanchard

Exponential-family random network (ERN) models specify a joint representation of both the dyads of a network and nodal characteristics. This class of models allow the nodal characteristics to be modelled as stochastic processes, expanding…

Methodology · Statistics 2013-03-07 Ian E. Fellows , Mark S. Handcock

We study the evolution of a random graph under the constraint that the diameter remain constant as the graph grows. We show that if the graph maintains the form of its link distribution it must be scale-free with exponent between 2 and 3.…

Statistical Mechanics · Physics 2007-05-23 Amit Puniyani , Rajan Lukose

We introduce a new random graph model motivated by biological questions relating to speciation. This random graph is defined as the stationary distribution of a Markov chain on the space of graphs on $\{1, \ldots, n\}$. The dynamics of this…

Probability · Mathematics 2019-06-24 François Bienvenu , Florence Débarre , Amaury Lambert

Exponential random graph models (ERGMs) are a widely used framework for network data, enabling hypothesis testing on the structural mechanisms underlying observed networks. Bayesian ERGMs provide principled uncertainty quantification and…

Methodology · Statistics 2026-05-26 Alberto Caimo , Isabella Gollini

We study a one parameter family of random graph models that spans a continuum between traditional random graphs of the Erd\H{o}s-R\'enyi type, where there is no underlying structure, and percolation models, where the possible edges are…

Probability · Mathematics 2008-04-02 Oskar Sandberg

We study a recent model for edge exchangeable random graphs introduced by Crane and Dempsey; in particular we study asymptotic properties of the random simple graph obtained by merging multiple edges. We study a number of examples, and show…

Probability · Mathematics 2017-08-02 Svante Janson

The generation of random graphs using edge swaps provides a reliable method to draw uniformly random samples of sets of graphs respecting some simple constraints, e.g. degree distributions. However, in general, it is not necessarily…

Social and Information Networks · Computer Science 2012-02-06 Lionel Tabourier , Camille Roth , Jean-Philippe Cointet

The purpose of this article is to present a general method to find limiting laws for some renormalized statistics on random permutations. The model considered here is Ewens sampling model, which generalizes uniform random permutations. We…

Probability · Mathematics 2013-10-28 Valentin Féray

In this paper we consider the Erd\H{o}s-R\'enyi random graph in the sparse regime in the limit as the number of vertices $n$ tends to infinity. We are interested in what this graph looks like when it contains many triangles, in two…

Probability · Mathematics 2026-01-27 Suman Chakraborty , Remco van der Hofstad , Frank den Hollander

We study the data-driven selection of causal graphical models using constraint-based algorithms, which determine the existence or non-existence of edges (causal connections) in a graph based on testing a series of conditional independence…

Methodology · Statistics 2026-04-29 Daniel Malinsky

The exponential family of models is defined in a general setting, not relying on probability theory. Some results of information geometry are shown to remain valid. Exponential families both of classical and of quantum mechanical…

Mathematical Physics · Physics 2015-06-03 Jan Naudts , Ben Anthonis

Exponential Random Graph Models (ERGM) behave peculiar in large networks with thousand(s) of actors (nodes). Standard models containing two-star or triangle counts as statistics are often unstable leading to completely full or empty…

Applications · Statistics 2016-04-19 Stephanie Thiemichen , Göran Kauermann

In [18] we analysed a simple undirected random graph subject to constraints on the total number of edges and the total number of triangles. We considered the dense regime in which the number of edges per vertex is proportional to the number…

Probability · Mathematics 2021-06-15 F. den Hollander , M. Mandjes , A. Roccaverde , N. J. Starreveld

Why do many modern neural-network-based graph generative models fail to reproduce typical real-world network characteristics, such as high triangle density? In this work we study the limitations of edge independent random graph models, in…

Machine Learning · Computer Science 2021-11-02 Sudhanshu Chanpuriya , Cameron Musco , Konstantinos Sotiropoulos , Charalampos E. Tsourakakis

We show that the random number $T_n$ of triangles in a random graph on $n$ vertices, with a strict constraint on the total number of edges, admits an expansion $T_n = an^3 + bn^2 + F_n$, where $a$ and $b$ are numbers, with the mean $\langle…

Combinatorics · Mathematics 2017-10-03 Charles Radin , Kui Ren , Lorenzo Sadun

This paper proves limit theorems for the number of monochromatic edges in uniform random colorings of general random graphs. These can be seen as generalizations of the birthday problem (what is the chance that there are two friends with…

Probability · Mathematics 2018-02-13 Bhaswar B. Bhattacharya , Persi Diaconis , Sumit Mukherjee

The analysis of large simple graphs with extreme values of the densities of edges and triangles has been extended to the statistical structure of typical graphs of fixed intermediate densities, by the use of large deviations of Erdoes-Renyi…

Probability · Mathematics 2022-03-31 Joe Neeman , Charles Radin , Lorenzo Sadun