Histogram Density Estimation

Histogram Density Estimation is a nonparametric density estimation method that approximates the probability density function of a random variable by partitioning the data space into discrete bins and normalizing the bin counts to form a piecewise constant density function.

97

Publications

7.9K

Citations

217

Authors

105

Institutions

Publications per year

2017–2026

11

Authors

217

  1. DW
    David W. Scott

    Rice University, United States

    6 publications · 1.1K citations

    6

    h-index

  2. LG
    László Györfi

    Budapest Institute, Hungary

    4 publications · 89 citations

    4

    h-index

  3. JV
    John Van Ryzin

    University of Wisconsin–Milwaukee, United States

    4 publications · 173 citations

    4

    h-index

  4. PH
    Peter Hall

    Australian National University, Australia

    3 publications · 133 citations

    3

    h-index

  5. JB
    Jan Beirlant

    KU Leuven, Belgium

    3 publications · 64 citations

    3

    h-index

1–5 of 217

Venues

  1. Journal of the American Statistical Association

    9 publications · 1.1K citations

    9

    h-index

  2. The Annals of Statistics

    6 publications · 623 citations

    6

    h-index

  3. 3

    h-index

  4. Neural Information Processing Systems

    Conference · 3 publications · 61 citations

    3

    h-index

  5. Communications in Statistics

    2 publications · 103 citations

    2

    h-index

1–5