Sequential Likelihood Ratio Tests

Sequential Likelihood Ratio Tests is a statistical hypothesis testing method that sequentially evaluates evidence by comparing the likelihood ratio of observed data against predetermined thresholds to decide between competing hypotheses, distinguishing itself from fixed-sample tests through its adaptive, ongoing evaluation of data as it becomes available.

124

Publications

6.8K

Citations

289

Authors

162

Institutions

Publications per year

2017–2026

15

Variants

Slrt

Authors

289

  1. TL
    Tze Leung Lai

    Stanford University, United States

    6 publications · 206 citations

    6

    h-index

  2. AK
    Alexey Kharin

    Belarusian State University, Belarus

    3 publications · 33 citations

    3

    h-index

  3. HP
    Hock Peng Chan

    National University of Singapore, Singapore

    3 publications · 111 citations

    3

    h-index

  4. AB
    Anindya Banerjee

    European University Institute, Italy

    2 publications · 747 citations

    2

    h-index

  5. JH
    James H. Stock

    Harvard University, United States

    2 publications · 747 citations

    2

    h-index

1–5 of 289

Venues

  1. The Annals of Statistics

    11 publications · 247 citations

    11

    h-index

  2. Sequential Analysis

    8 publications · 439 citations

    8

    h-index

  3. IEEE Transactions on Information Theory

    6 publications · 179 citations

    6

    h-index

  4. Biometrics

    5 publications · 256 citations

    5

    h-index

  5. The Annals of Mathematical Statistics

    5 publications · 295 citations

    5

    h-index

1–5