Large ball probabilities, Gaussian comparison and anti-concentration

Friedrich Götze, Alexey Naumov, Vladimir Spokoiny, Vladimir Ulyanov

    Research output: Contribution to journalArticlepeer-review

    7 Citations (Scopus)

    Abstract

    We derive tight non-asymptotic bounds for the Kolmogorov distance between the probabilities of two Gaussian elements to hit a ball in a Hilbert space. The key property of these bounds is that they are dimension-free and depend on the nuclear (Schatten-one) norm of the difference between the covariance operators of the elements and on the norm of the mean shift. The obtained bounds significantly improve the bound based on Pinsker's inequality via the Kullback-Leibler divergence. We also establish an anti-concentration bound for a squared norm of a non-centered Gaussian element in Hilbert space. The paper presents a number of examples motivating our results and applications of the obtained bounds to statistical inference and to high-dimensional CLT.

    Original languageEnglish
    Pages (from-to)2538-2563
    Number of pages26
    JournalBernoulli
    Volume25
    Issue number4 A
    DOIs
    Publication statusPublished - 2019

    Keywords

    • Dimension free bounds
    • Gaussian anti-concentration inequalities
    • Gaussian comparison
    • High-dimensional CLT
    • High-dimensional inference
    • Schatten norm

    Fingerprint

    Dive into the research topics of 'Large ball probabilities, Gaussian comparison and anti-concentration'. Together they form a unique fingerprint.

    Cite this