pith. sign in

arxiv: 1805.01720 · v1 · pith:2IQ7I6RRnew · submitted 2018-05-04 · 🧮 math.PR · math.AP· math.ST· stat.TH

Regularity of solutions of the Stein equation and rates in the multivariate central limit theorem

classification 🧮 math.PR math.APmath.STstat.TH
keywords alphadeltamultivariateorderequationolderregularitystein
0
0 comments X
read the original abstract

Consider the multivariate Stein equation $\Delta f - x\cdot \nabla f = h(x) - E h(Z)$, where $Z$ is a standard $d$-dimensional Gaussian random vector, and let $f\_h$ be the solution given by Barbour's generator approach. We prove that, when $h$ is $\alpha$-H\"older ($0<\alpha\leq1$), all derivatives of order $2$ of $f\_h$ are $\alpha$-H\"older {\it up to a $\log$ factor}; in particular they are $\beta$-H\"older for all $\beta \in (0, \alpha)$, hereby improving existing regularity results on the solution of the multivariate Gaussian Stein equation. For $\alpha=1$, the regularity we obtain is optimal, as shown by an example given by Rai\v{c} \cite{raivc2004multivariate}. As an application, we prove a near-optimal Berry-Esseen bound of the order $\log n/\sqrt n$ in the classical multivariate CLT in $1$-Wasserstein distance, as long as the underlying random variables have finite moment of order $3$. When only a finite moment of order $2+\delta$ is assumed ($0<\delta<1$), we obtain the optimal rate in $\mathcal O(n^{-\frac{\delta}{2}})$. All constants are explicit and their dependence on the dimension $d$ is studied when $d$ is large.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Wasserstein-p Central Limit Theorem Rates: From Local Dependence to Markov Chains

    math.PR 2026-01 unverdicted novelty 8.0

    The paper proves the first optimal O(n^{-1/2}) Wasserstein-1 CLT rates for locally dependent sequences and geometrically ergodic Markov chains, plus new W_p rates for p greater than or equal to 2 under mild moments, w...

  2. Gaussian Approximation for Asynchronous Q-learning

    stat.ML 2026-04 unverdicted novelty 7.0

    Derived rates of order up to n^{-1/6} log^4(n S A) for the high-dimensional CLT of averaged asynchronous Q-learning iterates, plus a general martingale-difference CLT.