  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.
