Change-point Detection

Change-Point Detection is a statistical methodology within time series analysis that identifies the specific point in a sequence of data where the underlying generative process undergoes a significant and abrupt change in distributional properties.

2.4K

Publications

149.9K

Citations

5K

Authors

1.8K

Institutions

Publications per year

2017–2026

688

Authors

5K

  1. AG
    Alexander G. Tartakovsky

    University of Southern California, United States

    25 publications · 1.8K citations

    21

    h-index

  2. MR
    Marion R. Reynolds

    Virginia Tech, United States

    21 publications · 1.6K citations

    18

    h-index

  3. PF
    Paul Fearnhead

    Lancaster University, United Kingdom

    20 publications · 3.5K citations

    17

    h-index

  4. MH
    Marie Hušková

    Charles University, Czechia

    17 publications · 843 citations

    16

    h-index

  5. LH
    Lajos Horváth

    University of Utah, United States

    21 publications · 1.2K citations

    16

    h-index

1–5 of 5K

Venues

  1. The Annals of Statistics

    50 publications · 4.6K citations

    36

    h-index

  2. Journal of Quality Technology

    46 publications · 4.4K citations

    34

    h-index

  3. Journal of the American Statistical Association

    40 publications · 6.2K citations

    25

    h-index

  4. arXiv (Cornell University)

    Repository · 72 publications · 2.2K citations

    25

    h-index

  5. Sequential Analysis

    40 publications · 1.4K citations

    25

    h-index

1–5