Correlation and autocorrelation of data on complex networks
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| Publicat a: | EPJ Data Science vol. 14, no. 1 (2025), p. 6 |
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| Publicat: |
Springer Nature B.V.
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| Matèries: | |
| Accés en línia: | Citation/Abstract Full Text - PDF |
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| 001 | 3159560704 | ||
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| 022 | |a 2193-1127 | ||
| 024 | 7 | |a 10.1140/epjds/s13688-025-00525-1 |2 doi | |
| 035 | |a 3159560704 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 242936 |2 nlm | ||
| 245 | 1 | |a Correlation and autocorrelation of data on complex networks | |
| 260 | |b Springer Nature B.V. |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 653 | |a Data processing | ||
| 653 | |a Data analysis | ||
| 653 | |a Spatial analysis | ||
| 653 | |a Fixing | ||
| 653 | |a Spatial data | ||
| 653 | |a Networks | ||
| 653 | |a Statistical analysis | ||
| 653 | |a Autocorrelation | ||
| 653 | |a Statistics | ||
| 653 | |a Social networks | ||
| 653 | |a Data science | ||
| 773 | 0 | |t EPJ Data Science |g vol. 14, no. 1 (2025), p. 6 | |
| 786 | 0 | |d ProQuest |t Agriculture Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3159560704/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3159560704/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |