Bayesian Spline Models

Bayesian Spline Models is a Bayesian nonparametric regression framework that employs spline basis functions with prior distributions on their coefficients and knot locations to flexibly model unknown functional forms while quantifying uncertainty.

60

Publications

5.8K

Citations

175

Authors

104

Institutions

Publications per year

2017–2026

13

Authors

175

  1. PL
    Philippe Lambert

    UCLouvain, Belgium

    3 publications · 181 citations

    3

    h-index

  2. CB
    Christopher Bronk Ramsey

    University of Oxford, United Kingdom

    3 publications · 1.6K citations

    3

    h-index

  3. HR
    Håvard Rue

    Norwegian University of Science and Technology, Norway

    3 publications · 110 citations

    3

    h-index

  4. TH
    Timothy Heaton

    University of Sheffield, United Kingdom

    3 publications · 1.6K citations

    3

    h-index

  5. AD
    Ara Darzi

    Imperial College London, United Kingdom

    2 publications · 64 citations

    2

    h-index

1–5 of 175

Venues

  1. Computational Statistics & Data Analysis

    CSDA · 7 publications · 676 citations

    7

    h-index

  2. 4

    h-index

  3. Journal of Computational and Graphical Statistics

    JCGS · 4 publications · 994 citations

    4

    h-index

  4. Statistics in Medicine

    4 publications · 86 citations

    4

    h-index

  5. Statistical Modelling

    3 publications · 90 citations

    3

    h-index

1–5