IDEAS home Printed from https://ideas.repec.org/a/spr/jotpro/v36y2023i3d10.1007_s10959-022-01225-6.html
   My bibliography  Save this article

Limit Theorems for Deviation Means of Independent and Identically Distributed Random Variables

Author

Listed:
  • Mátyás Barczy

    (University of Szeged)

  • Zsolt Páles

    (University of Debrecen)

Abstract

We derive a strong law of large numbers, a central limit theorem, a law of the iterated logarithm and a large deviation theorem for so-called deviation means of independent and identically distributed random variables. (For the strong law of large numbers, we suppose only pairwise independence instead of (total) independence.) The class of deviation means is a special class of M-estimators or more generally extremum estimators, which are well studied in statistics. The assumptions of our limit theorems for deviation means seem to be new and weaker than the known ones for M-estimators in the literature. In particular, our results on the strong law of large numbers and on the central limit theorem generalize the corresponding ones for quasi-arithmetic means due to de Carvalho (Am Stat 70(3):270–274, 2016) and the ones for Bajraktarević means due to Barczy and Burai (Aequ Math 96(2):279–305, 2022).

Suggested Citation

  • Mátyás Barczy & Zsolt Páles, 2023. "Limit Theorems for Deviation Means of Independent and Identically Distributed Random Variables," Journal of Theoretical Probability, Springer, vol. 36(3), pages 1626-1666, September.
  • Handle: RePEc:spr:jotpro:v:36:y:2023:i:3:d:10.1007_s10959-022-01225-6
    DOI: 10.1007/s10959-022-01225-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10959-022-01225-6
    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/s10959-022-01225-6?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. Miguel de Carvalho, 2016. "Mean, What do You Mean?," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 270-274, July.
    2. Miguel Arcones, 2006. "Large deviations for M-estimators," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 58(1), pages 21-52, March.
    3. Rubin, Herman & Rukhin, Andrew L., 1983. "Convergence rates of large deviations probabilities for point estimators," Statistics & Probability Letters, Elsevier, vol. 1(4), pages 197-202, June.
    Full references (including those not matched with items on IDEAS)

    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. Feehan, Dennis & Wrigley-Field, Elizabeth, 2020. "How do populations aggregate?," SocArXiv 2fkw3, Center for Open Science.
    2. Arcones Miguel A., 2007. "Minimax estimators of the coverage probability of the impermissible error for a location family," Statistics & Risk Modeling, De Gruyter, vol. 25(3), pages 173-215, July.
    3. Curto, José Dias & Serrasqueiro, Pedro, 2022. "Averaging financial ratios," Finance Research Letters, Elsevier, vol. 48(C).
    4. Guijing, Chen, 1996. "Optimal convergence rates and asymptotic efficiency of point estimators under truncated distribution families," Statistics & Probability Letters, Elsevier, vol. 30(4), pages 321-331, November.
    5. Guerrero, Victor M. & Solis-Lemus, Claudia, 2020. "A generalized measure of dispersion," Statistics & Probability Letters, Elsevier, vol. 164(C).
    6. Otsu, Taisuke, 2011. "Moderate deviations of generalized method of moments and empirical likelihood estimators," Journal of Multivariate Analysis, Elsevier, vol. 102(8), pages 1203-1216, September.
    7. Miguel Arcones, 2006. "Large deviations for M-estimators," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 58(1), pages 21-52, March.
    8. Yuichi Akaoka & Kazuki Okamura & Yoshiki Otobe, 2022. "Bahadur efficiency of the maximum likelihood estimator and one-step estimator for quasi-arithmetic means of the Cauchy distribution," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(5), pages 895-923, October.
    9. Adam Gorajek, 2022. "Quasilinear‐mean regression," Journal of Economic Surveys, Wiley Blackwell, vol. 36(5), pages 1288-1310, December.
    10. Clive Hunt & Ross Taplin, 2019. "Aggregation of Incidence and Intensity Risk Variables to Achieve Reconciliation," Risks, MDPI, vol. 7(4), pages 1-14, October.
    11. J. Fu & Gang Li & D. Zhao, 1993. "On large deviation expansion of distribution of maximum likelihood estimator and its application in large sample estimation," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 45(3), pages 477-498, September.
    12. Dennis Feehan & Elizabeth Wrigley-Field, 2021. "How do populations aggregate?," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 44(15), pages 363-378.

    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:36:y:2023:i:3:d:10.1007_s10959-022-01225-6. 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.