Changepoint inference for Erdős–Rényi random graphs

Elena Yudovina, Moulinath Banerjee, George Michailidis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


We formulate a model for the off-line estimation of a changepoint in a network setting. The framework naturally allows the parameter space (network size) to grow with the number of observations. We compute the signal-to-noise ratio detectability threshold, and establish the dependence of the rate of convergence and asymptotic distribution on the network size and parameters. In addition, we show that inference can be adaptive, i.e. asymptotically correct confidence intervals can be computed based on the data. We apply the method to the question of whether US Congress has abruptly become more polarized at some point in recent history.

Original languageEnglish (US)
Title of host publicationStochastic Models, Statistics and Their Applications, 2015
EditorsEwaryst Rafajłowicz, Krzysztof Szajowski, Ansgar Steland
PublisherSpringer New York LLC
Number of pages9
ISBN (Electronic)9783319138800
StatePublished - 2015
Event12th Workshop on Stochastic Models, Statistics and their Applications, 2015 - Wrocław, Poland
Duration: Feb 16 2015Feb 20 2015

Publication series

NameSpringer Proceedings in Mathematics and Statistics
ISSN (Print)2194-1009
ISSN (Electronic)2194-1017


Other12th Workshop on Stochastic Models, Statistics and their Applications, 2015

Bibliographical note

Publisher Copyright:
© Springer International Publishing Switzerland 2015.


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