Optimal Experimental Designs

Optimal Experimental Designs is a methodological framework in the context of inverse problems that systematically determines the most informative experimental configurations to minimize uncertainty and maximize the identifiability of model parameters.

2.1K

Publications

128K

Citations

4.2K

Authors

1.4K

Institutions

Publications per year

2017–2026

372

Variants

OedOptimal Experimental Design

Authors

4.2K

  1. HD
    Holger Dette

    Ruhr University Bochum, Germany

    75 publications · 2.7K citations

    32

    h-index

  2. AC
    Anthony C. Atkinson

    London School of Economics and Political Science, United Kingdom

    27 publications · 3.3K citations

    23

    h-index

  3. WK
    Weng Kee Wong

    University of California, Los Angeles, United States

    43 publications · 1K citations

    22

    h-index

  4. PG
    Peter Goos

    University of Antwerp, Belgium

    31 publications · 1.7K citations

    21

    h-index

  5. BJ
    Bradley Jones

    SAS Institute (United States), United States

    23 publications · 1.5K citations

    18

    h-index

1–5 of 4.2K

Venues

  1. Technometrics

    102 publications · 14.7K citations

    48

    h-index

  2. The Annals of Statistics

    84 publications · 4.6K citations

    36

    h-index

  3. Journal of the American Statistical Association

    71 publications · 4.3K citations

    35

    h-index

  4. Journal of Statistical Planning and Inference

    122 publications · 4.1K citations

    33

    h-index

  5. Biometrika

    69 publications · 9.8K citations

    32

    h-index

1–5