Nonparametric Density Estimation

Nonparametric Density Estimation is a statistical method for estimating probability density functions without assuming a fixed parametric form, distinguishing it from parametric approaches by relying solely on the data to determine the shape of the distribution.

781

Publications

74K

Citations

1.4K

Authors

632

Institutions

Publications per year

2017–2026

96

Authors

1.4K

  1. PH
    Peter Hall

    Australian National University, Australia

    22 publications · 1.9K citations

    18

    h-index

  2. DW
    David W. Scott

    Rice University, United States

    12 publications · 1.6K citations

    12

    h-index

  3. JS
    J. S. Marron

    University of North Carolina at Chapel Hill, United States

    8 publications · 434 citations

    8

    h-index

  4. FC
    Fabienne Comte

    Université Paris Cité, France

    7 publications · 130 citations

    7

    h-index

  5. GR
    George R. Terrell

    Rice University, United States

    7 publications · 1.2K citations

    7

    h-index

1–5 of 1.4K

Venues

  1. The Annals of Statistics

    72 publications · 8.8K citations

    43

    h-index

  2. Journal of the American Statistical Association

    60 publications · 8.6K citations

    38

    h-index

  3. Computational Statistics & Data Analysis

    CSDA · 21 publications · 583 citations

    16

    h-index

  4. Journal of nonparametric statistics

    30 publications · 802 citations

    16

    h-index

  5. arXiv (Cornell University)

    Repository · 22 publications · 3.7K citations

    15

    h-index

1–5