Likelihood Approximation

Likelihood Approximation is a computational method that belongs to the class of statistical techniques used to estimate likelihood functions, distinguished by its reliance on simplifying assumptions or numerical procedures to approximate intractable or complex likelihoods when exact evaluation is impractical.

180

Publications

15.4K

Citations

343

Authors

217

Institutions

Publications per year

2017–2026

36

Authors

343

  1. CJ
    Charles J. Geyer

    University of Minnesota, United States

    3 publications · 1.2K citations

    3

    h-index

  2. GS
    Govind S. Mudholkar

    University of Rochester, United States

    3 publications · 46 citations

    3

    h-index

  3. OE
    Ole E. Barndorff–Nielsen

    Aarhus University, Denmark

    3 publications · 460 citations

    3

    h-index

  4. JL
    Jens Ledet Jensen

    Aarhus University, Denmark

    3 publications · 117 citations

    3

    h-index

  5. GM
    Geert Molenberghs

    Hasselt University, Belgium

    3 publications · 65 citations

    3

    h-index

1–5 of 343

Venues

  1. Biometrika

    12 publications · 977 citations

    12

    h-index

  2. Journal of the American Statistical Association

    14 publications · 1.1K citations

    12

    h-index

  3. arXiv (Cornell University)

    Repository · 8 publications · 264 citations

    8

    h-index

  4. Journal of Computational and Graphical Statistics

    JCGS · 6 publications · 1.6K citations

    6

    h-index

  5. The Astrophysical Journal

    ApJ · 5 publications · 182 citations

    5

    h-index

1–5