Estimation of on- and off-time distributions in a dynamic Erdős-Rényi random graph

Fuente: arXiv
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Autores principales: Mandjes, Michel, Wang, Jiesen
Formato: Preprint
Publicado: 2024
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author Mandjes, Michel
Wang, Jiesen
author_facet Mandjes, Michel
Wang, Jiesen
contents In this paper we consider a dynamic Erdős-Rényi graph in which edges, according to an alternating renewal process, change from present to absent and vice versa. The objective is to estimate the on- and off-time distributions while only observing the aggregate number of edges. This inverse problem is dealt with, in a parametric context, by setting up an estimator based on the method of moments. We provide conditions under which the estimator is asymptotically normal, and we point out how the corresponding covariance matrix can be identified. It is also demonstrated how to adapt the estimation procedure if alternative subgraph counts are observed, such as the number of wedges or triangles.
format Preprint
id arxiv_https___arxiv_org_abs_2401_14531
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Estimation of on- and off-time distributions in a dynamic Erdős-Rényi random graph
Mandjes, Michel
Wang, Jiesen
Statistics Theory
Probability
05C80, 62M09, 62F12
In this paper we consider a dynamic Erdős-Rényi graph in which edges, according to an alternating renewal process, change from present to absent and vice versa. The objective is to estimate the on- and off-time distributions while only observing the aggregate number of edges. This inverse problem is dealt with, in a parametric context, by setting up an estimator based on the method of moments. We provide conditions under which the estimator is asymptotically normal, and we point out how the corresponding covariance matrix can be identified. It is also demonstrated how to adapt the estimation procedure if alternative subgraph counts are observed, such as the number of wedges or triangles.
title Estimation of on- and off-time distributions in a dynamic Erdős-Rényi random graph
topic Statistics Theory
Probability
05C80, 62M09, 62F12
url https://arxiv.org/abs/2401.14531