Gaussian stationary processes over graphs, general frame and maximum likelihood identification
Statistics Theory
2012-03-23 v3 Statistics Theory
Abstract
In this paper, using spectral theory of Hilbertian operators, we study ARMA Gaussian processes indexed by graphs. We extend Whittle maximum likelihood estimation of the parameters for the corresponding spectral density and show their asymptotic optimality.
Cite
@article{arxiv.1104.3664,
title = {Gaussian stationary processes over graphs, general frame and maximum likelihood identification},
author = {Thibault Espinasse and Fabrice Gamboa and Jean-Michel Loubes},
journal= {arXiv preprint arXiv:1104.3664},
year = {2012}
}