Central limit theorem for functionals of a generalized self-similar Gaussian process
Probability
2016-12-06 v2
Abstract
We consider a class of self-similar, continuous Gaussian processes that do not necessarily have stationary increments. We prove a version of the Breuer-Major theorem for this class, that is, subject to conditions on the covariance function, a generic functional of the process increments converges in law to a Gaussian random variable. The proof is based on the Fourth Moment Theorem. We give examples of five non-stationary processes that satisfy these conditions.
Cite
@article{arxiv.1508.02756,
title = {Central limit theorem for functionals of a generalized self-similar Gaussian process},
author = {Daniel Harnett and David Nualart},
journal= {arXiv preprint arXiv:1508.02756},
year = {2016}
}