High Quantile Estimation

High Quantile Estimation is a statistical methodology within extreme value theory that specifically addresses the estimation of quantiles in the upper tail of a distribution, where the focus is on accurately characterizing rare and extreme events beyond typical sample observations.

115

Publications

5.7K

Citations

243

Authors

185

Institutions

Publications per year

2017–2026

44

Authors

243

  1. PE
    Paul Embrechts

    ETH Zurich, Switzerland

    6 publications · 364 citations

    6

    h-index

  2. MI
    M. Ivette Gomes

    University of Lisbon, Portugal

    5 publications · 236 citations

    5

    h-index

  3. LD
    Laurens de Haan

    Erasmus University Rotterdam, Netherlands

    5 publications · 944 citations

    5

    h-index

  4. MD
    Matthias Degen

    ETH Zurich, Switzerland

    4 publications · 250 citations

    4

    h-index

  5. DL
    Deyuan Li

    Fudan University, China

    3 publications · 170 citations

    3

    h-index

1–5 of 243

Venues

  1. 9

    h-index

  2. Water Resources Research

    4 publications · 386 citations

    4

    h-index

  3. Journal of Multivariate Analysis

    3 publications · 44 citations

    3

    h-index

  4. Astin Bulletin

    3 publications · 216 citations

    3

    h-index

  5. SSRN Electronic Journal

    Repository · 3 publications · 53 citations

    3

    h-index

1–5