A test on the L-moments of the degree distribution of a Barabási–Albert network for detecting nodal and edge degradation
Document Type
Article
Publication Date
2-2018
Abstract
This research creates a test of hypothesis to detect subtle degradation within a Barabási–Albert network attributable to nodal or edge degradation. For this purpose, degradation is defined as the removal of the nodes or edges within the network that changes the structure of the network and subsequently its degree distribution. To achieve the study’s objective, L-moments from the degree distribution of the Barabási–Albert network are used to create a multivariate test of hypothesis. This is then followed by an analysis of the sensitivity of the test to changes within the network based on proportion of edge and nodal deletion to investigate how quickly the test detects a degrading Barabási–Albert network. Results from the sensitivity analysis show that the multivariate test using L-scale, L-skewness and L-kurtosis is able to detect degradation at a faster rate in comparison to a univariate test alone.
Source Publication
Journal of Complex Networks (ISSN 2051-1310 | eISSN 2051-1329)
Recommended Citation
Fairul Mohd-Zaid, Christine M. Schubert Kabban, Richard F. Deckro, A test on the L-moments of the degree distribution of a Barabási–Albert network for detecting nodal and edge degradation, Journal of Complex Networks, Volume 6, Issue 1, February 2018, Pages 24–53, https://doi.org/10.1093/comnet/cnx020
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Journal of Complex Networks is published by Oxford University Press.