Conditional Likelihood

Conditional Likelihood is a probabilistic measure that quantifies the likelihood of observed data given a specific set of parameter values and a conditional probability model, distinguishing itself from marginal or joint likelihoods by explicitly incorporating the dependence of outcomes on given conditions or prior events.

540

Publications

83.8K

Citations

1K

Authors

511

Institutions

Publications per year

2017–2026

66

Authors

1K

  1. AM
    Andrew McCallum

    University of Massachusetts Amherst, United States

    6 publications · 842 citations

    6

    h-index

  2. JQ
    Jing Qin

    National Institute of Allergy and Infectious Diseases, United States

    6 publications · 236 citations

    6

    h-index

  3. DW
    Donald W. K. Andrews

    Yale University, United States

    6 publications · 579 citations

    6

    h-index

  4. BG
    Bruce G. Lindsay

    Pennsylvania State University, United States

    5 publications · 580 citations

    5

    h-index

  5. MJ
    Marcelo J. Moreira

    Escola Brasileira de Economia e Finanças, Brazil

    5 publications · 1.2K citations

    5

    h-index

1–5 of 1K

Venues

  1. Biometrika

    31 publications · 4.1K citations

    23

    h-index

  2. Biometrics

    29 publications · 3.1K citations

    19

    h-index

  3. Statistics in Medicine

    22 publications · 835 citations

    16

    h-index

  4. Journal of the American Statistical Association

    20 publications · 3.6K citations

    15

    h-index

  5. 14

    h-index

1–5