Identification and estimation of stochastic blockmodels

This paper contains new identification results for undirected weighted stochastic blockmodels. They are sharper than the ones available to date and the arguments underlying them are constructive. A nonparametric estimation framework that is computationally attractive is presented and the associated distribution theory is derived. Numerical experiments are reported on.