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
Parents
60
SHCal20 Southern Hemisphere Calibration, 0–55,000 Years cal BP
Alan Hogg, Timothy Heaton, Quan Hua et al. · Radiocarbon · 2020 · 1.4K citations · Full text
Stefan Lang, Andreas Brezger · Journal of Computational and Graphical Statistics · 2004 · 883 citations
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104
University of Oxford
Oxford, United Kingdom
6 h-index
13 publications
1.7K citations
University of Michigan
Ann Arbor, United States
4 h-index
7 publications
222 citations
Ludwig-Maximilians-Universität München
Munich, Germany
4 h-index
8 publications
2.7K citations
UCLouvain
Louvain-la-Neuve, Belgium
3 h-index
5 publications
355 citations

UNSW Sydney
Sydney, Australia
3 h-index
6 publications
4.5K citations

Imperial College London
London, United Kingdom
3 h-index
25 publications
796 citations
University of Sheffield
Sheffield, United Kingdom
3 h-index
5 publications
3.1K citations
Queen's University Belfast
Belfast, United Kingdom
2 h-index
4 publications
3.1K citations
1–8 of 104
CSDA · 7 publications · 676 citations
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4 publications · 189 citations
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JCGS · 4 publications · 994 citations
4
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4 publications · 86 citations
4
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3 publications · 90 citations
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