Log-likelihood Functions

Log-Likelihood Functions is a mathematical function that belongs to the class of likelihood-based statistical functions, distinguished by being the natural logarithm of the likelihood function, thereby transforming products of probabilities into sums for analytical and computational convenience in parameter estimation and inference.

1.4K

Publications

130.5K

Citations

3.6K

Authors

1.1K

Institutions

Publications per year

2017–2026

299

Variants

Log-likelihoodLog-likelihood Function

Authors

3.6K

  1. YB
    Yoshua Bengio

    Université de Montréal, Canada

    11 publications · 2.6K citations

    11

    h-index

  2. JA
    Jeffrey A. Fessler

    University of Michigan, United States

    7 publications · 1.6K citations

    7

    h-index

  3. OE
    Ole E. Barndorff–Nielsen

    Aarhus University, Denmark

    6 publications · 449 citations

    6

    h-index

  4. MI
    Michael I. Jordan

    University of California, Berkeley, United States

    5 publications · 515 citations

    5

    h-index

  5. AO
    Alfred O. Hero

    University of Michigan, United States

    5 publications · 1.2K citations

    5

    h-index

1–5 of 3.6K

Venues

  1. Journal of the American Statistical Association

    51 publications · 15K citations

    33

    h-index

  2. arXiv (Cornell University)

    Repository · 70 publications · 13.9K citations

    30

    h-index

  3. Biometrika

    33 publications · 5.1K citations

    25

    h-index

  4. IEEE Transactions on Signal Processing

    31 publications · 2.7K citations

    22

    h-index

  5. The Annals of Statistics

    28 publications · 1.8K citations

    21

    h-index

1–5