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Quantitative Breuer-Major Theorems

Author

Listed:
• Ivan Nourdin

() (Laboratoire de Probabilités et Modèles Aléatoires, Université Pierre et Marie Curie)

• Giovanni Peccati

() (University of Luxembourg)

• Mark Podolskij

() (ETH Zürich and CREATES)

Abstract

We consider sequences of random variables of the type $S_n= n^{-1/2} \sum_{k=1}^n f(X_k)$, $n\geq 1$, where $X=(X_k)_{k\in \Z}$ is a $d$-dimensional Gaussian process and $f: \R^d \rightarrow \R$ is a measurable function. It is known that, under certain conditions on $f$ and the covariance function $r$ of $X$, $S_n$ converges in distribution to a normal variable $S$. In the present paper we derive several explicit upper bounds for quantities of the type $|\E[h(S_n)] -\E[h(S)]|$, where $h$ is a sufficiently smooth test function. Our methods are based on Malliavin calculus, on interpolation techniques and on the Stein's method for normal approximation. The bounds deduced in our paper depend only on $\E[f^2(X_1)]$ and on simple infinite series involving the components of $r$. In particular, our results generalize and refine some classic CLTs by Breuer-Major, Giraitis-Surgailis and Arcones, concerning the normal approximation of partial sums associated with Gaussian-subordinated time-series.

Suggested Citation

• Ivan Nourdin & Giovanni Peccati & Mark Podolskij, 2010. "Quantitative Breuer-Major Theorems," CREATES Research Papers 2010-22, Department of Economics and Business Economics, Aarhus University.
• Handle: RePEc:aah:create:2010-22
as

File URL: ftp://ftp.econ.au.dk/creates/rp/10/rp10_22.pdf

References listed on IDEAS

as
1. León, José & Ludeña, Carenne, 2007. "Limits for weighted p-variations and likewise functionals of fractional diffusions with drift," Stochastic Processes and their Applications, Elsevier, vol. 117(3), pages 271-296, March.
2. Breuer, Péter & Major, Péter, 1983. "Central limit theorems for non-linear functionals of Gaussian fields," Journal of Multivariate Analysis, Elsevier, vol. 13(3), pages 425-441, September.
3. Barndorff-Nielsen, Ole E. & Corcuera, José Manuel & Podolskij, Mark, 2009. "Power variation for Gaussian processes with stationary increments," Stochastic Processes and their Applications, Elsevier, vol. 119(6), pages 1845-1865, June.
4. Corinne Berzin & José León, 2007. "Estimating the Hurst Parameter," Statistical Inference for Stochastic Processes, Springer, vol. 10(1), pages 49-73, January.
5. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2009. "Multipower Variation for Brownian Semistationary Processes," CREATES Research Papers 2009-21, Department of Economics and Business Economics, Aarhus University.
Full references (including those not matched with items on IDEAS)

Citations

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Cited by:

1. Bardet, Jean-Marc & Surgailis, Donatas, 2013. "Moment bounds and central limit theorems for Gaussian subordinated arrays," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 457-473.
2. Ivan Nourdin & David Nualart & Rola Zintout, 2016. "Multivariate central limit theorems for averages of fractional Volterra processes and applications to parameter estimation," Statistical Inference for Stochastic Processes, Springer, vol. 19(2), pages 219-234, July.
3. repec:eee:spapps:v:127:y:2017:i:10:p:3412-3446 is not listed on IDEAS
4. Marie Kratz & Sreekar Vadlamani, 2016. "CLT for Lipschitz-Killing curvatures of excursion sets of Gaussian random fields," Working Papers hal-01373091, HAL.
5. Pham, Viet-Hung, 2013. "On the rate of convergence for central limit theorems of sojourn times of Gaussian fields," Stochastic Processes and their Applications, Elsevier, vol. 123(6), pages 2158-2174.

Keywords

Berry-Esseen bounds; Breuer-Major central limit theorems; Gaussian processes; Interpolation; Malliavin calculus; Stein’s method;

JEL classification:

• C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
• C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General

NEP fields

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