Total variation estimates in the Breuer-Major theorem

Abstract

This paper provides estimates for the convergence rate of the total variation distance in the framework of the Breuer-Major theorem, assuming some smoothness properties of the underlying function. The results are proved by applying new bounds for the total variation distance between a random variable expressed as a divergence and a standard Gaussian random variable, which are derived by a combination of techniques of Malliavin calculus and Stein's method. The representation of a functional of a Gaussian sequence as a divergence is established by introducing a shift operator on the expansion in Hermite polynomials. Some applications to the asymptotic behavior of power variations of the fractional Brownian motions and to the estimation of the Hurst parameter using power variations are presented.

References in corpus (4)

• Central limit theorems for sequences of multiple stochastic integrals
• Asymptotic behavior of weighted quadratic and cubic variations of fractional Brownian motion
• Optimal Berry-Esseen rates on the Wiener space: the barrier of third and fourth cumulants
• The rate of convergence of estimate for Hurst index of fractional Brownian motion involved into stochastic differential equation

Cited by in corpus (3)

• A Central Limit Theorem for the stochastic wave equation with fractional noise
• Quantitative normal approximations for the stochastic fractional heat equation
• Rate of convergence for the weighted Hermite variations of the fractional Brownian motion