Nonparametric Maximum Likelihood Estimation

Nonparametric Maximum Likelihood Estimation is a statistical inference method that belongs to the class of nonparametric estimation techniques, distinguished by its maximization of the likelihood function over a completely specified space of probability distributions without assuming a finite-dimensional parametric form for the underlying distribution.

462

Publications

32.9K

Citations

733

Authors

414

Institutions

Publications per year

2017–2026

47

Authors

733

  1. DZ
    Donglin Zeng

    University of North Carolina at Chapel Hill, United States

    11 publications · 714 citations

    11

    h-index

  2. FJ
    Francisco J. Samaniego

    University of California, Davis, United States

    12 publications · 485 citations

    11

    h-index

  3. PG
    Piet Groeneboom

    Delft University of Technology, Netherlands

    10 publications · 786 citations

    10

    h-index

  4. JA
    Jon A. Wellner

    University of Washington, United States

    9 publications · 932 citations

    9

    h-index

  5. YV
    Y. Vardi

    AT&T (United States), United States

    7 publications · 1.1K citations

    7

    h-index

1–5 of 733

Venues

  1. The Annals of Statistics

    63 publications · 6.6K citations

    39

    h-index

  2. Journal of the American Statistical Association

    54 publications · 4.5K citations

    31

    h-index

  3. Biometrics

    34 publications · 2.2K citations

    25

    h-index

  4. Biometrika

    32 publications · 2K citations

    23

    h-index

  5. Journal of Computational and Graphical Statistics

    JCGS · 11 publications · 590 citations

    11

    h-index

1–5