Stable Laws

Stable Laws is a class of probability distributions characterized by the property that the linear combination of two independent random variables with the same distribution follows the same distribution up to location and scale parameters, making them invariant under convolution and forming the attractors in generalized central limit theorems.

202

Publications

10.1K

Citations

257

Authors

182

Institutions

Publications per year

2017–2026

12

Variants

Lévy Stable Distributions

Authors

257

  1. VV
    V. V. Uchaikin

    Ulyanovsk State University, Russia

    5 publications · 333 citations

    5

    h-index

  2. VA
    Vedat Akgiray

    Louisiana State University, United States

    5 publications · 569 citations

    5

    h-index

  3. IA
    Ioannis A. Koutrouvelis

    Virginia Commonwealth University, United States

    5 publications · 851 citations

    5

    h-index

  4. MM
    Mark M. Meerschaert

    Michigan State University, United States

    4 publications · 96 citations

    4

    h-index

  5. VP
    Vygantas Paulauskas

    Vilnius University, Lithuania

    2 publications · 40 citations

    3

    h-index

1–5 of 257

Venues

  1. The Annals of Probability

    18 publications · 627 citations

    15

    h-index

  2. Theory of Probability and Its Applications

    11 publications · 324 citations

    10

    h-index

  3. Electronic Journal of Probability

    EJP · 8 publications · 275 citations

    8

    h-index

  4. 7

    h-index

  5. Journal of Applied Probability

    JAP · 7 publications · 84 citations

    7

    h-index

1–5