Mode Estimation

Mode Estimation is a statistical inference method that identifies the most probable value(s) in a probability density function by locating the peak(s) of a kernel density estimate, distinguishing it from other density-based estimation techniques through its focus on maximal density points as representatives of central tendency or underlying data structures.

489

Publications

41.5K

Citations

1.1K

Authors

561

Institutions

Publications per year

2017–2026

107

Authors

1.1K

  1. PF
    Patrick Flandrin

    École Normale Supérieure de Lyon, France

    11 publications · 4.4K citations

    11

    h-index

  2. JW
    John W. Pierre

    University of Wyoming, United States

    7 publications · 494 citations

    7

    h-index

  3. CR
    Christopher R. Genovese

    Carnegie Mellon University, United States

    6 publications · 404 citations

    6

    h-index

  4. AB
    Abdel‐Ouahab Boudraa

    École Navale, France

    6 publications · 365 citations

    6

    h-index

  5. GS
    Gastón Schlotthauer

    Universidad Nacional de Entre Ríos, Argentina

    5 publications · 2.6K citations

    5

    h-index

1–5 of 1.1K

Venues

  1. The Annals of Statistics

    16 publications · 1.3K citations

    15

    h-index

  2. Mechanical Systems and Signal Processing

    MSSP · 12 publications · 1.1K citations

    12

    h-index

  3. IEEE Signal Processing Letters

    8 publications · 346 citations

    8

    h-index

  4. 8

    h-index

  5. The Journal of the Acoustical Society of America

    JASA · 8 publications · 354 citations

    8

    h-index

1–5