arXiv Analytics

Sign in

arXiv:1606.08208 [math.PR]AbstractReferencesReviewsResources

The winding of stationary Gaussian processes

Jeremiah Buckley, Naomi Feldheim

Published 2016-06-27Version 1

This paper studies the winding of a continuously differentiable Gaussian stationary process $f:\mathbb{R}\to\mathbb{C}$ in the interval $[0,T]$. We give formulae for the mean and the variance of this random variable. The variance is shown to always grow at least linearly with $T$, and conditions for it to be asymptotically linear or quadratic are given. Moreover, we show that if the covariance function together with its second derivative are in $L^2(\mathbb{R})$, then the winding obeys a central limit theorem. These results correspond to similar results for zeroes of real-valued stationary Gaussian functions by Cuzick, Slud and others.

Related articles: Most relevant | Search more
arXiv:0805.1198 [math.PR] (Published 2008-05-08)
Exactness of martingale approximation and the central limit theorem
arXiv:0911.2905 [math.PR] (Published 2009-11-15)
A strictly stationary, "causal," 5-tuplewise independent counterexample to the central limit theorem
arXiv:math/0509682 [math.PR] (Published 2005-09-29, updated 2006-09-25)
Central limit theorem for stationary linear processes