Shrinkage Estimation

Shrinkage Estimation is a statistical estimation method that belongs to the class of biased estimation techniques and is distinguished by its deliberate reduction of estimation variance through the imposition of constraints or penalties that pull estimates toward a pre-specified value or structure, often resulting in improved overall accuracy relative to unbiased estimators in finite samples.

532

Publications

198.5K

Citations

882

Authors

467

Institutions

Publications per year

2017–2026

90

Authors

882

  1. MW
    Michael Wolf

    University of Zurich, Switzerland

    15 publications · 2K citations

    15

    h-index

  2. SE
    S. Ejaz Ahmed

    Brock University, Canada

    17 publications · 484 citations

    14

    h-index

  3. OL
    Olivier Ledoit

    University of Zurich, Switzerland

    14 publications · 2.1K citations

    14

    h-index

  4. AK
    A. K. Md. Ehsanes Saleh

    Carleton University, Canada

    12 publications · 385 citations

    11

    h-index

  5. EI
    Edward I. George

    University of Pennsylvania, United States

    9 publications · 432 citations

    9

    h-index

1–5 of 882

Venues

  1. Journal of the American Statistical Association

    25 publications · 7.7K citations

    19

    h-index

  2. Journal of Multivariate Analysis

    26 publications · 1K citations

    19

    h-index

  3. The Annals of Statistics

    17 publications · 1.8K citations

    16

    h-index

  4. Communication in Statistics- Theory and Methods

    26 publications · 929 citations

    15

    h-index

  5. Computational Statistics & Data Analysis

    CSDA · 14 publications · 497 citations

    13

    h-index

1–5