Likelihood-based Confidence Intervals

Likelihood-Based Confidence Intervals is a statistical inference method that constructs confidence intervals by inverting the likelihood ratio test, wherein the interval consists of parameter values for which the log-likelihood does not fall below a threshold determined by a specified significance level, thereby distinguishing it from other interval estimation techniques through its direct reliance on the likelihood function's shape.

122

Publications

9.7K

Citations

194

Authors

151

Institutions

Publications per year

2017–2026

9

Variants

Likelihood-based Confidence Regions

Authors

194

  1. SX
    Song Xi Chen

    Peking University, China

    5 publications · 535 citations

    5

    h-index

  2. LP
    Liang Peng

    Georgia Institute of Technology, United States

    3 publications · 58 citations

    3

    h-index

  3. AH
    A. H. Welsh

    Australian National University, Australia

    3 publications · 77 citations

    3

    h-index

  4. LA
    Luis A. Escobar

    Louisiana State University, United States

    3 publications · 391 citations

    3

    h-index

  5. JW
    Jianrong Wu

    St. Jude Children's Research Hospital, United States

    3 publications · 107 citations

    3

    h-index

1–5 of 194

Venues

  1. Biometrika

    13 publications · 2.7K citations

    12

    h-index

  2. 8

    h-index

  3. Statistics in Medicine

    6 publications · 266 citations

    6

    h-index

  4. Technometrics

    5 publications · 127 citations

    5

    h-index

  5. Biometrics

    5 publications · 241 citations

    5

    h-index

1–5