Change Point Detection in a Dynamic Stochastic Blockmodel

Autor:	François G. Meyer, Peter Wills
Rok vydání:	2019
Předmět:	Theoretical computer science Computer science Monte Carlo method Test statistic Topological graph theory Graph (abstract data type) Graph model Change detection Distance
Zdroj:	Complex Networks and Their Applications VIII ISBN: 9783030366865 COMPLEX NETWORKS (1)
DOI:	10.1007/978-3-030-36687-2_18
Popis:	We study a change point detection scenario for a dynamic community graph model, which is formed by adding new vertices and randomly attaching them to the existing nodes. The goal of this work is to design a test statistic to detect the merging of communities without solving the problem of identifying the communities. We propose a test that can ascertain when the connectivity between the balanced communities is changing. In addition to the theoretical analysis of the test statistic, we perform Monte Carlo simulations of the dynamic stochastic blockmodel to demonstrate that our test can detect changes in graph topology, and we study a dynamic social-contact graph.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::cedc44c641abf01c40e708cee25d4856 https://doi.org/10.1007/978-3-030-36687-2_18 Zobrazit plný text záznamu