Bayesian Nonparametric Calibration

Bayesian Nonparametric Calibration is a statistical calibration framework that belongs to the class of Bayesian calibration methods and is distinguished by its use of nonparametric prior distributions to flexibly model the calibration function without assuming a fixed parametric form.

4

Publications

117

Citations

14

Authors

11

Institutions

Publications per year

2017–2026

2

Authors

14

  1. LJ
    Lawrence Joseph

    McGill University, Canada

    1 publications · 28 citations

    1

    h-index

  2. FB
    Federico Bassetti

    University of Pavia, Italy

    1 publications · 58 citations

    1

    h-index

  3. JY
    Jielong Yang

    Jilin University, China

    1 publications · 20 citations

    1

    h-index

  4. SH
    Shahram Heydari

    McGill University, Canada

    1 publications · 28 citations

    1

    h-index

  5. CE
    Caitlin E. Buck

    University of Sheffield, United Kingdom

    1 publications · 11 citations

    1

    h-index

1–5 of 14

Venues

  1. 1

    h-index

  2. Bayesian Analysis

    1 publications · 11 citations

    1

    h-index

  3. Analytic Methods in Accident Research

    1 publications · 28 citations

    1

    h-index

  4. IEEE Internet of Things Journal

    1 publications · 20 citations

    1

    h-index

1–5