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Bayesian Approximate Kernel Regression with Variable Selection

Nonlinear kernel regression models are often used in statistics and machine learning because they are more accurate than linear models. Variable selection for kernel regression models is a challenge partly because, unlike the linear regression setting, there is no clear concept of an effect size for...

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Detalhes bibliográficos
Publicado no:J Am Stat Assoc
Main Authors: Crawford, Lorin, Wood, Kris C., Zhou, Xiang, Mukherjee, Sayan
Formato: Artigo
Idioma:Inglês
Publicado em: 2018
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6383716/
https://ncbi.nlm.nih.gov/pubmed/30799887
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2017.1361830
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