IDEAS home Printed from https://ideas.repec.org/a/spr/jotpro/v29y2016i2d10.1007_s10959-014-0590-8.html
   My bibliography  Save this article

Classical and Free Fourth Moment Theorems: Universality and Thresholds

Author

Listed:
  • Ivan Nourdin

    (Université du Luxembourg)

  • Giovanni Peccati

    (Université du Luxembourg)

  • Guillaume Poly

    (Université de Rennes 1)

  • Rosaria Simone

    (Université du Luxembourg
    Università degli Studi della Basilicata)

Abstract

Let $$X$$ X be a centered random variable with unit variance and zero third moment, and such that $$\mathrm{IE}[X^4] \ge 3$$ IE [ X 4 ] ≥ 3 . Let $$\{F_n {:}\, n\ge 1\}$$ { F n : n ≥ 1 } denote a normalized sequence of homogeneous sums of fixed degree $$d\ge 2$$ d ≥ 2 , built from independent copies of $$X$$ X . Under these minimal conditions, we prove that $$F_n$$ F n converges in distribution to a standard Gaussian random variable if and only if the corresponding sequence of fourth moments converges to $$3$$ 3 . The statement is then extended (mutatis mutandis) to the free probability setting. We shall also discuss the optimality of our conditions in terms of explicit thresholds, as well as establish several connections with the so-called universality phenomenon of probability theory. Both in the classical and free probability frameworks, our results extend and unify previous Fourth Moment Theorems for Gaussian and semicircular approximations. Our techniques are based on a fine combinatorial analysis of higher moments for homogeneous sums.

Suggested Citation

  • Ivan Nourdin & Giovanni Peccati & Guillaume Poly & Rosaria Simone, 2016. "Classical and Free Fourth Moment Theorems: Universality and Thresholds," Journal of Theoretical Probability, Springer, vol. 29(2), pages 653-680, June.
  • Handle: RePEc:spr:jotpro:v:29:y:2016:i:2:d:10.1007_s10959-014-0590-8
    DOI: 10.1007/s10959-014-0590-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10959-014-0590-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10959-014-0590-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rotar', V. I., 1979. "Limit theorems for polylinear forms," Journal of Multivariate Analysis, Elsevier, vol. 9(4), pages 511-530, December.
    2. de Jong, Peter, 1990. "A central limit theorem for generalized multilinear forms," Journal of Multivariate Analysis, Elsevier, vol. 34(2), pages 275-289, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yuta Koike, 2023. "High-Dimensional Central Limit Theorems for Homogeneous Sums," Journal of Theoretical Probability, Springer, vol. 36(1), pages 1-45, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yuta Koike, 2023. "High-Dimensional Central Limit Theorems for Homogeneous Sums," Journal of Theoretical Probability, Springer, vol. 36(1), pages 1-45, March.
    2. Antoine, Bertille & Lavergne, Pascal, 2023. "Identification-robust nonparametric inference in a linear IV model," Journal of Econometrics, Elsevier, vol. 235(1), pages 1-24.
    3. Kasprzak, Mikołaj J., 2020. "Stein’s method for multivariate Brownian approximations of sums under dependence," Stochastic Processes and their Applications, Elsevier, vol. 130(8), pages 4927-4967.
    4. Peng, Hanxiang & Schick, Anton, 2018. "Asymptotic normality of quadratic forms with random vectors of increasing dimension," Journal of Multivariate Analysis, Elsevier, vol. 164(C), pages 22-39.
    5. Barton, N.H. & Etheridge, A.M. & Véber, A., 2017. "The infinitesimal model: Definition, derivation, and implications," Theoretical Population Biology, Elsevier, vol. 118(C), pages 50-73.
    6. Bartels, Knut, 1998. "A model specification test," SFB 373 Discussion Papers 1998,109, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    7. Shuyang Bai & Murad S. Taqqu, 2016. "The Universality of Homogeneous Polynomial Forms and Critical Limits," Journal of Theoretical Probability, Springer, vol. 29(4), pages 1710-1727, December.
    8. Ivan Nourdin & Giovanni Peccati & Xiaochuan Yang, 2022. "Multivariate Normal Approximation on the Wiener Space: New Bounds in the Convex Distance," Journal of Theoretical Probability, Springer, vol. 35(3), pages 2020-2037, September.
    9. Gao, Jiti & Hong, Yongmiao, 2007. "Central limit theorems for weighted quadratic forms of dependent processes with applications in specification testing," MPRA Paper 11977, University Library of Munich, Germany, revised Dec 2007.
    10. Konrad Menzel, 2021. "Central Limit Theory for Models of Strategic Network Formation," Papers 2111.01678, arXiv.org.
    11. Nicolas Privault, 2024. "Asymptotic Analysis of k-Hop Connectivity in the 1D Unit Disk Random Graph Model," Methodology and Computing in Applied Probability, Springer, vol. 26(4), pages 1-26, December.
    12. Youri Davydov & Vladimir Rotar, 2009. "On Asymptotic Proximity of Distributions," Journal of Theoretical Probability, Springer, vol. 22(1), pages 82-98, March.
    13. Nourdin, Ivan & Poly, Guillaume, 2015. "An invariance principle under the total variation distance," Stochastic Processes and their Applications, Elsevier, vol. 125(6), pages 2190-2205.
    14. Fan, Yanqin & Ullah, Aman, 1999. "Asymptotic Normality of a Combined Regression Estimator," Journal of Multivariate Analysis, Elsevier, vol. 71(2), pages 191-240, November.
    15. Konrad Menzel, 2021. "Bootstrap With Cluster‐Dependence in Two or More Dimensions," Econometrica, Econometric Society, vol. 89(5), pages 2143-2188, September.
    16. Robins, James M. & Li, Lingling & Tchetgen, Eric Tchetgen & van der Vaart, Aad, 2016. "Asymptotic normality of quadratic estimators," Stochastic Processes and their Applications, Elsevier, vol. 126(12), pages 3733-3759.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jotpro:v:29:y:2016:i:2:d:10.1007_s10959-014-0590-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.