Correlation and Autocorrelation of Data on Complex Networks

Fuente: arXiv
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Autore principale: Arthur, Rudy
Natura: Preprint
Pubblicazione: 2024
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author Arthur, Rudy
author_facet Arthur, Rudy
contents Networks where each node has one or more associated numerical values are common in applications. This work studies how summary statistics used for the analysis of spatial data can be applied to non-spatial networks for the purposes of exploratory data analysis. We focus primarily on Moran-type statistics and discuss measures of global autocorrelation, local autocorrelation and global correlation. We introduce null models based on fixing edges and permuting the data or fixing the data and permuting the edges. We demonstrate the use of these statistics on real and synthetic node-valued networks.
format Preprint
id arxiv_https___arxiv_org_abs_2405_05125
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Correlation and Autocorrelation of Data on Complex Networks
Arthur, Rudy
Social and Information Networks
Physics and Society
Networks where each node has one or more associated numerical values are common in applications. This work studies how summary statistics used for the analysis of spatial data can be applied to non-spatial networks for the purposes of exploratory data analysis. We focus primarily on Moran-type statistics and discuss measures of global autocorrelation, local autocorrelation and global correlation. We introduce null models based on fixing edges and permuting the data or fixing the data and permuting the edges. We demonstrate the use of these statistics on real and synthetic node-valued networks.
title Correlation and Autocorrelation of Data on Complex Networks
topic Social and Information Networks
Physics and Society
url https://arxiv.org/abs/2405.05125