Bayesian Generalized Additive Models
Bayesian Generalized Additive Models is a statistical modeling framework that extends generalized additive models by incorporating Bayesian inference to estimate smooth functional relationships between predictors and a response variable while accounting for uncertainty through prior distributions.
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2.9K
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181
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126
Institutions
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2017–2026
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51
Shape constrained additive models
Natalya Pya, Simon N. Wood · Statistics and Computing · 2014 · 313 citations · Full text
Both low and high temperature may increase the risk of stroke mortality
Renjie Chen, Cuicui Wang, Xia Meng et al. · Neurology · 2013 · 169 citations · Full text
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126

Universität Innsbruck
Innsbruck, Austria
4 h-index
9 publications
796 citations
UCLouvain
Louvain-la-Neuve, Belgium
2 h-index
3 publications
105 citations

Centre National de la Recherche Scientifique
Paris, France
2 h-index
6 publications
140 citations
Columbia University
New York, United States
2 h-index
2 publications
54 citations

University of St Andrews
St Andrews, United Kingdom
2 h-index
2 publications
32 citations

Huazhong University of Science and Technology
Wuhan, China
2 h-index
6 publications
126 citations
University of Zurich
Zurich, Switzerland
2 h-index
3 publications
59 citations
Humboldt-Universität zu Berlin
Berlin, Germany
2 h-index
2 publications
86 citations
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JSS · 4 publications · 322 citations
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2 publications · 68 citations
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CSDA · 2 publications · 72 citations
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JCGS · 2 publications · 170 citations
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2 publications · 118 citations
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