Shape-constrained Estimation

Shape-Constrained Estimation is a nonparametric statistical method that restricts the estimated function to satisfy prespecified shape properties such as monotonicity, convexity, or concavity, thereby combining flexibility in functional form with economically or scientifically justified structural constraints.

88

Publications

4.4K

Citations

187

Authors

126

Institutions

Publications per year

2017–2026

30

Variants

Shape-restricted Estimation

Authors

187

  1. MC
    Mary C. Meyer

    Colorado State University, United States

    6 publications · 304 citations

    6

    h-index

  2. JL
    Joël L. Horowitz

    University of Iowa, United States

    4 publications · 162 citations

    4

    h-index

  3. BS
    Bodhisattva Sen

    Columbia University, United States

    4 publications · 146 citations

    4

    h-index

  4. CD
    Chuangyin Dang

    City University of Hong Kong, Hong Kong SAR China

    3 publications · 102 citations

    3

    h-index

  5. AG
    Adityanand Guntuboyina

    University of California, Berkeley, United States

    3 publications · 107 citations

    3

    h-index

1–5 of 187

Venues

  1. Journal of Econometrics

    6 publications · 615 citations

    6

    h-index

  2. The Annals of Statistics

    6 publications · 360 citations

    6

    h-index

  3. Statistical Science

    4 publications · 136 citations

    4

    h-index

  4. 4

    h-index

  5. 3

    h-index

1–5