Stable Limit Theorems

Stable Limit Theorems is a theoretical framework in probability theory that characterizes the convergence of normalized sums of independent and identically distributed random variables to stable distributions, distinguished from other limit theorems by allowing for heavy-tailed distributions and non-Gaussian limiting behavior.

263

Publications

12.2K

Citations

371

Authors

244

Institutions

Publications per year

2017–2026

17

Authors

371

  1. AJ
    Adam Jakubowski

    Nicolaus Copernicus University, Poland

    7 publications · 279 citations

    7

    h-index

  2. ST
    Svetlozar T. Rachev

    University of California, Santa Barbara, United States

    7 publications · 209 citations

    7

    h-index

  3. TM
    Thomas Mikosch

    University of Copenhagen, Denmark

    5 publications · 1.6K citations

    5

    h-index

  4. MS
    Murad S. Taqqu

    Boston University, United States

    4 publications · 1.4K citations

    4

    h-index

  5. RB
    Robert Blumenthal

    National Institutes of Health, United States

    3 publications · 542 citations

    3

    h-index

1–5 of 371

Venues

  1. The Annals of Probability

    23 publications · 1.6K citations

    17

    h-index

  2. Stochastic Processes and their Applications

    12 publications · 411 citations

    12

    h-index

  3. Journal of Applied Probability

    JAP · 10 publications · 316 citations

    10

    h-index

  4. Statistics & Probability Letters

    9 publications · 171 citations

    9

    h-index

  5. Transactions of the American Mathematical Society

    TRAN · 9 publications · 842 citations

    9

    h-index

1–5