Copula Estimation

Copula Estimation is a statistical method that belongs to the class of nonparametric techniques used to model the dependence structure between random variables by estimating a copula function, which separates the marginal distributions from the joint distribution to capture the underlying association pattern without assuming a specific parametric form.

1.7K

Publications

89.7K

Citations

3.1K

Authors

1.4K

Institutions

Publications per year

2017–2026

600

Authors

3.1K

  1. CG
    Christian Genest

    Université Laval, Canada

    29 publications · 6.6K citations

    26

    h-index

  2. CC
    Claudia Czado

    Technical University of Munich, Germany

    29 publications · 4.3K citations

    19

    h-index

  3. FD
    Fabrizio Durante

    Free University of Bozen-Bolzano, Italy

    22 publications · 605 citations

    17

    h-index

  4. TE
    Takeshi Emura

    National Central University, Taiwan

    21 publications · 569 citations

    17

    h-index

  5. HJ
    Harry Joe

    University of British Columbia, Canada

    17 publications · 2.1K citations

    16

    h-index

1–5 of 3.1K

Venues

  1. Journal of Multivariate Analysis

    64 publications · 4.2K citations

    34

    h-index

  2. Computational Statistics & Data Analysis

    CSDA · 53 publications · 3.2K citations

    27

    h-index

  3. Insurance Mathematics and Economics

    44 publications · 3.8K citations

    25

    h-index

  4. SSRN Electronic Journal

    Repository · 57 publications · 1.9K citations

    24

    h-index

  5. Journal of the American Statistical Association

    18 publications · 2.5K citations

    16

    h-index

1–5