Interval Width Optimization

Interval Width Optimization is a statistical method that systematically minimizes the width of a credible interval while maintaining a specified level of posterior coverage, thereby enhancing precision in Bayesian parameter estimation.

5

Publications

252

Citations

18

Authors

11

Institutions

Publications per year

2017–2026

2

Authors

18

  1. DS
    Dongqi Su

    Changchun Institute of Optics, Fine Mechanics and Physics, China

    1 publications · 17 citations

    1

    h-index

  2. CL
    Chenchen Lin

    Fuzhou University, China

    1 publications · 127 citations

    1

    h-index

  3. DR
    Dabing Ren

    Kunming University of Science and Technology, China

    1 publications · 127 citations

    1

    h-index

  4. YL
    Yi‐Zeng Liang

    Central South University, China

    1 publications · 127 citations

    1

    h-index

  5. RF
    R.C. Forbes

    Loughborough University, United Kingdom

    1 publications · 21 citations

    1

    h-index

1–5 of 18

Venues

  1. arXiv (Cornell University)

    Repository · 1 publications · 17 citations

    1

    h-index

  2. Nondestructive Testing And Evaluation

    1 publications · 23 citations

    1

    h-index

  3. The Analyst

    1 publications · 127 citations

    1

    h-index

  4. IEEE Transactions on Power Systems

    1 publications · 64 citations

    1

    h-index

  5. International Journal of Computer Mathematics

    1 publications · 21 citations

    1

    h-index

1–5