Registered Networks: Localization and Heterogeneity
Teague Henry , University of North Carolina at Chapel Hill, Psychology and Neuroscience
Registered networks, networks where the identities of the nodes are known and relevant, are common in certain areas of social science. Brain connectivity networks are a prime example, as are psychometric networks, formed from the estimated relations between psychological constructs. In this talk, we present two related methods for analyzing samples of registered networks. The first, the network based statistic jackknife, allows for the localization of network statistic based inferences. This alleviates the issue of inference equifinality, where vastly differing network configurations can lead to the same conclusions. The second, the network homogeneity test, evaluates if a sample of registered networks comes from the same generating distribution. This test is based in graph limit theory and does not require the assumption of a specific generating distribution (e.g. ER, small world, etc…). Application areas of these tests are discussed, and several simulations are presented.
February, 19 2018 | 12:45 pm - 2:00 pm | Gross Hall 230E