Correlation and autocorrelation of data on complex networks
Abstract 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-t...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2025-01-01
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| Series: | EPJ Data Science |
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| Online Access: | https://doi.org/10.1140/epjds/s13688-025-00525-1 |
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| _version_ | 1832586030486650880 |
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| author | Rudy Arthur |
| author_facet | Rudy Arthur |
| author_sort | Rudy Arthur |
| collection | DOAJ |
| description | Abstract 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 | Article |
| id | doaj-art-ffb18f34ea574b46a2a5980e9720b8ad |
| institution | Kabale University |
| issn | 2193-1127 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EPJ Data Science |
| spelling | doaj-art-ffb18f34ea574b46a2a5980e9720b8ad2025-01-26T12:20:04ZengSpringerOpenEPJ Data Science2193-11272025-01-0114112010.1140/epjds/s13688-025-00525-1Correlation and autocorrelation of data on complex networksRudy Arthur0Department of Computer Science, University of ExeterAbstract 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.https://doi.org/10.1140/epjds/s13688-025-00525-1NetworksSpatial AnalysisCorrelationAutocorrelation |
| spellingShingle | Rudy Arthur Correlation and autocorrelation of data on complex networks EPJ Data Science Networks Spatial Analysis Correlation Autocorrelation |
| title | Correlation and autocorrelation of data on complex networks |
| title_full | Correlation and autocorrelation of data on complex networks |
| title_fullStr | Correlation and autocorrelation of data on complex networks |
| title_full_unstemmed | Correlation and autocorrelation of data on complex networks |
| title_short | Correlation and autocorrelation of data on complex networks |
| title_sort | correlation and autocorrelation of data on complex networks |
| topic | Networks Spatial Analysis Correlation Autocorrelation |
| url | https://doi.org/10.1140/epjds/s13688-025-00525-1 |
| work_keys_str_mv | AT rudyarthur correlationandautocorrelationofdataoncomplexnetworks |