Trimmed Estimators

Trimmed Estimators is a robust statistical method that belongs to the class of location or scale estimators and is distinguished by the exclusion of a specified proportion of extreme observations from both tails of an ordered sample before computing the estimate.

253

Publications

15.2K

Citations

350

Authors

213

Institutions

Publications per year

2017–2026

15

Authors

350

  1. RR
    Rand R. Wilcox

    University of Southern California, United States

    20 publications · 666 citations

    15

    h-index

  2. HJ
    H. J. Keselman

    University of Manitoba, Canada

    14 publications · 570 citations

    13

    h-index

  3. AG
    Alfonso Gordaliza

    Universidad de Valladolid, Spain

    8 publications · 476 citations

    8

    h-index

  4. LM
    Lisa M. Lix

    University of Manitoba, Canada

    7 publications · 394 citations

    7

    h-index

  5. LÁ
    Luis Ángel García-Escudero

    Universidad de Valladolid, Spain

    6 publications · 383 citations

    6

    h-index

1–5 of 350

Venues

  1. Journal of the American Statistical Association

    36 publications · 2.7K citations

    25

    h-index

  2. The Annals of Statistics

    14 publications · 1.5K citations

    13

    h-index

  3. Computational Statistics & Data Analysis

    CSDA · 15 publications · 716 citations

    13

    h-index

  4. 8

    h-index

  5. Statistics & Probability Letters

    8 publications · 196 citations

    8

    h-index

1–5