Credibility With Sparse Data

Credibility with Sparse Data is a methodological framework within credibility theory that quantifies the reliability of estimates or predictions when limited observational data are available, distinguished by its integration of prior knowledge and data-scarce adjustments to maintain statistical robustness.

7

Publications

110

Citations

18

Authors

6

Institutions

Publications per year

2017–2026

1

Authors

18

  1. NN
    Nurzhan Nurushev

    Vrije Universiteit Amsterdam, Netherlands

    1 publications · 12 citations

    1

    h-index

  2. RW
    Ruyan Wang

    Chongqing University of Posts and Telecommunications, China

    1 publications · 10 citations

    1

    h-index

  3. EB
    Eduard Belitser

    Vrije Universiteit Amsterdam, Netherlands

    1 publications · 12 citations

    1

    h-index

  4. JD
    Joshua D. Angrist

    Massachusetts Institute of Technology, United States

    1 publications · 16 citations

    1

    h-index

  5. DW
    Dapeng Wu

    Chongqing University of Posts and Telecommunications, China

    1 publications · 10 citations

    1

    h-index

1–5 of 18

Venues

  1. Insurance Mathematics and Economics

    2 publications · 51 citations

    2

    h-index

  2. National Bureau of Economic Research

    Repository · 1 publications · 16 citations

    1

    h-index

  3. Sensors

    1 publications · 10 citations

    1

    h-index

  4. Astin Bulletin

    1 publications · 11 citations

    1

    h-index

  5. arXiv (Cornell University)

    Repository · 1 publications · 12 citations

    1

    h-index

1–5