The study of random graphs and networks had an explosive development
in the last couple of decades. Meanwhile, techniques for the statistical analysis of
sequences of networks were less developed. In this paper, we focus on networks
sequences with a fixed number of labeled nodes and study some statistical problems
in a nonparametric framework. We introduce natural notions of center and a depth
function for networks that evolve in time. We develop several statistical techniques
including testing, supervised and unsupervised classification, and some notions of
principal component sets in the space of networks. Some examples and asymptotic
results are given, as well as two real data examples.

EB00000004341K

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• Nonparametric statistics of dynamic networks with distinguishable nodes