Abstract

We compute explicit bounds in the Gaussian approximation of functionals of infinite Rademacher sequences. Our tools involve Stein's method, as well as the use of appropriate discrete Malliavin operators. As the bounds are given in terms of Malliavin operators, no coupling construction is required. When the functional depends only on the first d coordinates of the Rademacher sequence, a simple sufficient condition for convergence to a normal distribution is derived. For finite quadratic forms, we obtain necessary and sufficient conditions. Although our approach does not require the classical use of exchangeable pairs, when the functional depends only on the first d coordinates of the Rademacher sequence we employ chaos expansion in order to construct an explicit exchangeable pair vector; the elements of the vector relate to the summands in the chaos decomposition and satisfy a linearity condition for the conditional expectation. Among several examples, such as random variables which depend on infinitely many Rademacher variables, we provide three main applications: (i) to CLTs for multilinear forms belonging to a fixed chaos, (ii) to the Gaussian approximation of weighted infinite 2-runs, and (iii) to the computation of explicit bounds in CLTs for multiple integrals over sparse sets. This last application provides an alternate proof (and several refinements) of a recent result by Blei and Janson.

Highlights

  • The connection between Stein’s method and the integration by parts formulae of stochastic analysis has been the object of a recent and quite fruitful study

  • The papers [25, 26, 27] deal with Stein’s method and Malliavin calculus in a Gaussian setting; in [28] one can find extensions involving density estimates and concentration inequalities; the paper [31] is devoted to explicit bounds, obtained by combining Malliavin calculus and Stein’s method in the framework of Poisson measures

  • Note that all these references contain examples and applications that were previously outside the scope of Stein’s method, as they involve functionals of infinitedimensional random fields for which the usual Stein-type techniques, which involve picking a random index from a finite set, seem inappropriate

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Summary

Introduction

The connection between Stein’s method (see e.g. [8, 36, 43, 44]) and the integration by parts formulae of stochastic analysis has been the object of a recent and quite fruitful study. The aim of this paper is to push this line of research one step further, by combining Stein’s method with an appropriate discrete version of Malliavin calculus, in order to study the normal approximation of the functionals of an infinite Rademacher sequence By this expression we mean a sequence X = {Xn : n 1} of i.i.d. random variables, such that P(X1 = 1) = P(X1 = −1) = 1/2. (iv) In the particular case of random variables belonging to a fixed chaos, that is, having the form of a (possibly infinite) series of multilinear forms of a fixed order, we will express our bounds in terms of norms of contraction operators (see Section 2.2) These objects play a central role in the normal and Gamma approximations of functionals of Gaussian fields (see [25, 26, 27, 30]) and Poisson measures (see [31, 32, 33]).

The setup
The star notation
Finding a chaotic decomposition
Discrete Malliavin calculus and a new chain rule
Stein’s method for normal approximation
Main bound
First examples
A general exchangeable pair construction
From twice differentiable functions to the Wasserstein distance
Explicit upper bounds and CLTs
More on finite quadratic forms
Motivation: infinite weighted runs
Normal approximation of sums of single and double integrals
Bounds for infinite 2-runs
General results
Fractional Cartesian products
Beyond the Rademacher case: a question by Blei and Janson
Full Text
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