Parametric Estimation

Parametric Estimation is a statistical inference method that belongs to the class of estimation techniques in which the underlying probability distribution is assumed to have a known functional form characterized by a finite set of parameters, distinguishing it from nonparametric and semiparametric approaches by requiring explicit specification of the distributional family.

1.9K

Publications

148.1K

Citations

3.3K

Authors

1.4K

Institutions

Publications per year

2017–2026

247

Variants

Parametric Inference

Authors

3.3K

  1. RJ
    Raymond J. Carroll

    Texas A&M University, United States

    17 publications · 1.6K citations

    16

    h-index

  2. WK
    Whitney K. Newey

    Massachusetts Institute of Technology, United States

    15 publications · 2.7K citations

    15

    h-index

  3. JL
    Joël L. Horowitz

    University of Iowa, United States

    12 publications · 1.4K citations

    12

    h-index

  4. PH
    Peter Hall

    Australian National University, Australia

    12 publications · 781 citations

    11

    h-index

  5. AD
    Aurore Delaigle

    The University of Melbourne, Australia

    10 publications · 478 citations

    10

    h-index

1–5 of 3.3K

Venues

  1. Journal of the American Statistical Association

    106 publications · 20.6K citations

    52

    h-index

  2. The Annals of Statistics

    78 publications · 10.1K citations

    45

    h-index

  3. 36

    h-index

  4. Econometrica

    35 publications · 9K citations

    31

    h-index

  5. Biometrika

    50 publications · 4.6K citations

    31

    h-index

1–5