Bartlett, TE;
(2017)
Network inference and community detection, based on covariance matrices, correlations and test statistics from arbitrary distributions.
Communications in Statistics - Theory and Methods
, 46
(18)
pp. 9150-9165.
10.1080/03610926.2016.1205624.
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Abstract
In this paper we propose methodology for inference of binary-valued adjacency matrices from various measures of the strength of association between pairs of network nodes, or more generally pairs of variables. This strength of association can be quantified by sample covariance and cor- relation matrices, and more generally by test-statistics and hypothesis test p-values from arbitrary distributions. Community detection methods such as block modelling typically require binary-valued adjacency matrices as a starting point. Hence, a main motivation for the methodology we propose is to obtain binary-valued adjacency matrices from such pairwise measures of strength of association between variables. The proposed methodology is applicable to large high-dimensional data-sets and is based on computationally efficient algorithms. We illustrate its utility in a range of contexts and data-sets.
| Type: | Article |
|---|---|
| Title: | Network inference and community detection, based on covariance matrices, correlations and test statistics from arbitrary distributions |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1080/03610926.2016.1205624 |
| Publisher version: | http://dx.doi.org/10.1080/03610926.2016.1205624 |
| Language: | English |
| Additional information: | © 2016 The Author(s). Published with license by Taylor & Francis Group, LLC This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/1507792 |
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