Change-Point Detection in Dynamic Networks with Missing Links

Fuente: arXiv
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Autori principali: Enikeeva, Farida, Klopp, Olga
Natura: Preprint
Pubblicazione: 2021
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author Enikeeva, Farida
Klopp, Olga
author_facet Enikeeva, Farida
Klopp, Olga
contents Structural changes occur in dynamic networks quite frequently and its detection is an important question in many situations such as fraud detection or cybersecurity. Real-life networks are often incompletely observed due to individual non-response or network size. In the present paper we consider the problem of change-point detection at a temporal sequence of partially observed networks. The goal is to test whether there is a change in the network parameters. Our approach is based on the Matrix CUSUM test statistic and allows growing size of networks. We show that the proposed test is minimax optimal and robust to missing links. We also demonstrate the good behavior of our approach in practice through simulation study and a real-data application.
format Preprint
id arxiv_https___arxiv_org_abs_2106_14470
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle Change-Point Detection in Dynamic Networks with Missing Links
Enikeeva, Farida
Klopp, Olga
Statistics Theory
Structural changes occur in dynamic networks quite frequently and its detection is an important question in many situations such as fraud detection or cybersecurity. Real-life networks are often incompletely observed due to individual non-response or network size. In the present paper we consider the problem of change-point detection at a temporal sequence of partially observed networks. The goal is to test whether there is a change in the network parameters. Our approach is based on the Matrix CUSUM test statistic and allows growing size of networks. We show that the proposed test is minimax optimal and robust to missing links. We also demonstrate the good behavior of our approach in practice through simulation study and a real-data application.
title Change-Point Detection in Dynamic Networks with Missing Links
topic Statistics Theory
url https://arxiv.org/abs/2106.14470