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We propose a random graph model with preferential attachment rule and \emph{edge-step functions} that govern the growth rate of the vertex set. We study the effect of these functions on the empirical degree distribution of these random…

Probability · Mathematics 2019-01-09 Caio Alves , Rodrigo Ribeiro , Remy Sanchis

Generating realistic artificial preference distributions is an important part of any simulation analysis of electoral systems. While this has been discussed in some detail in the context of a single electoral district, many electoral…

Computer Science and Game Theory · Computer Science 2017-06-30 Geoffrey Pritchard , Mark C. Wilson

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

Preferential attachment is often suggested to be the underlying mechanism of the growth of a network, largely due to that many real networks are, to a certain extent, scale-free. However, such attribution is usually made under debatable…

Applications · Statistics 2025-09-16 Clement Lee

We propose an extension of the preferential attachment scheme by allowing the connecting probability to depend on time t. We estimate the parameters involved in the model by minimizing the expected squared difference between the number of…

Methodology · Statistics 2022-04-26 Bo Zhang , Hanyang Tian , Guangming Pan

This work is devoted to P\'olya-Young urns, a class of periodic P\'olya urns of importance in the analysis of Young tableaux. We provide several extension of the previous results of Banderier, Marchal and Wallner [Ann. Prob. (2020)] on…

Probability · Mathematics 2024-06-28 Markus Kuba

We give a common description of Simon, Barab\'asi--Albert, II-PA and Price growth models, by introducing suitable random graph processes with preferential attachment mechanisms. Through the II-PA model, we prove the conditions for which the…

Probability · Mathematics 2016-02-29 Angelica Pachon , Federico Polito , Laura Sacerdote

This paper presents a comprehensive analysis of the degree statistics in models for growing networks where new nodes enter one at a time and attach to one earlier node according to a stochastic rule. The models with uniform attachment,…

Statistical Mechanics · Physics 2015-05-13 C. Godreche , H. Grandclaude , J. M. Luck

In classical urn models, one usually draws one ball with replacement at each time unit and then adds one ball of the same colour. Given a weight sequence $(w_k)_{k\in\N}$, the probability of drawing a ball of a certain colour is…

Probability · Mathematics 2012-01-18 Mickaël Launay

Adaptive randomly reinforced urn (ARRU) is a two-color urn model where the updating process is defined by a sequence of non-negative random vectors $\{(D_{1,n}, D_{2,n});n\geq1\}$ and randomly evolving thresholds which utilize accruing…

Probability · Mathematics 2019-09-27 Giacomo Aletti , Andrea Ghiglietti , Anand Vidyashankar

Computing over compressed data combines the space saving of data compression with efficient support for queries directly on the compressed representation. Such data structures are widely applied in text indexing and have been successfully…

Data Structures and Algorithms · Computer Science 2025-06-27 Ziad Ismaili Alaoui , Namrata , Sebastian Wild

Many important real-world networks manifest "small-world" properties such as scale-free degree distributions, small diameters, and clustering. The most common model of growth for these networks is "preferential attachment", where nodes…

Quantitative Methods · Quantitative Biology 2009-11-13 Samarth Swarup , Les Gasser

Numerous works have been proposed to generate random graphs preserving the same properties as real-life large scale networks. However, many real networks are better represented by hypergraphs. Few models for generating random hypergraphs…

Social and Information Networks · Computer Science 2021-03-03 Frédéric Giroire , Nicolas Nisse , Thibaud Trolliet , Małgorzata Sulkowska

The aim of this paper is to develop a method for proving almost sure convergence in Gromov-Hausodorff-Prokhorov topology for a class of models of growing random graphs that generalises R\'emy's algorithm for binary trees. We describe the…

Probability · Mathematics 2020-02-25 Delphin Sénizergues

Complex networks in different areas exhibit degree distributions with heavy upper tail. A preferential attachment mechanism in a growth process produces a graph with this feature. We herein investigate a variant of the simple preferential…

Probability · Mathematics 2018-04-18 Angelica Pachon , Laura Sacerdote , Shuyi Yang

A family of models of growing hypergraphs with preferential rules of new linking is introduced and studied. The model hypergraphs evolve via the hyperedge-based growth as well as the node-based one, thus generalizing the…

Physics and Society · Physics 2023-09-04 Dahae Roh , Kwang-Il Goh

This paper analyzes key properties of networks generated by geometric preferential attachment. We establish that the expected number of triangles is proportional to that of the standard preferential attachment model, with a proportionality…

Probability · Mathematics 2025-11-25 Chenxu Feng , Yifan Li

Inside the discipline of graph theory exists an extension known as the hypergraph. This generalization of graphs includes vertices along with hyperedges consisting of collections of two or more vertices. One well-studied application of this…

Probability · Mathematics 2024-03-19 Joshua Sparks

In this article we presented a brief study of the main network models with growth and preferential attachment. Such models are interesting because they present several characteristics of real systems. We started with the classical model…

Physics and Society · Physics 2020-07-06 Gabriel G. Piva , Fabiano L. Ribeiro , Angelica S. Mata

We complete the study of the model introduced in [11]. It is a two-color urn model with multiple drawing and random (non-balanced) time-dependent reinforcement matrix. The number of sampled balls at each time-step is random. We identify the…

Statistics Theory · Mathematics 2022-08-05 Irene Crimaldi , Pierre-Yves Louis , Ida G. Minelli
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