Date of Original Version

10-2013

Type

Article

Rights Management

© Institute of Mathematical Statistics, 2013

Abstract or Description

Variational methods for parameter estimation are an active research area, potentially offering computationally tractable heuristics with theoretical performance bounds. We build on recent work that applies such methods to network data, and establish asymptotic normality rates for parameter estimates of stochastic blockmodel data, by either maximum likelihood or variational estimation. The result also applies to various sub-models of the stochastic blockmodel found in the literature.

DOI

10.1214/13-AOS1124

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Published In

Annals of Statistics, 41, 4, 1922-1943.