Robust Bayesian Sample Size

Robust Bayesian Sample Size is a Bayesian sample size determination method that ensures reliable and stable inference under model misspecification or uncertainty by incorporating prior robustness and sensitivity analysis into the design of experiments.

12

Publications

355

Citations

22

Authors

12

Institutions

Publications per year

2017–2026

1

Authors

22

  1. FD
    Fulvio De Santis

    Sapienza University of Rome, Italy

    4 publications · 194 citations

    4

    h-index

  2. PB
    Pierpaolo Brutti

    Sapienza University of Rome, Italy

    2 publications · 83 citations

    2

    h-index

  3. SG
    Stefania Gubbiotti

    Sapienza University of Rome, Italy

    1 publications · 69 citations

    1

    h-index

  4. SM
    Saurabh Mukhopadhyay

    Indiana University – Purdue University Indianapolis, United States

    1 publications · 17 citations

    1

    h-index

  5. MB
    Mark Bender

    General Motors (United States), United States

    1 publications · 50 citations

    1

    h-index

1–5 of 22

Venues

  1. Journal of Statistical Planning and Inference

    4 publications · 102 citations

    4

    h-index

  2. 2

    h-index

  3. Computational Statistics & Data Analysis

    CSDA · 2 publications · 30 citations

    2

    h-index

  4. Statistics in Medicine

    1 publications · 69 citations

    1

    h-index

  5. Microelectronics Reliability

    1 publications · 50 citations

    1

    h-index

1–5