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Nonparametric regression with adaptive truncation via a convex hierarchical penalty
We consider the problem of nonparametric regression with a potentially large number of covariates. We propose a convex, penalized estimation framework that is particularly well suited to high-dimensional sparse additive models and combines the appealing features of finite basis representation and sm...
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| Publicat a: | Biometrika |
|---|---|
| Autors principals: | , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Oxford University Press
2019
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6691776/ https://ncbi.nlm.nih.gov/pubmed/31427821 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/biomet/asy056 |
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