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Nonparametric Independence Screening in Sparse Ultra-High Dimensional Additive Models
A variable screening procedure via correlation learning was proposed in Fan and Lv (2008) to reduce dimensionality in sparse ultra-high dimensional models. Even when the true model is linear, the marginal regression can be highly nonlinear. To address this issue, we further extend the correlation le...
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| Main Authors: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2011
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3263471/ https://ncbi.nlm.nih.gov/pubmed/22279246 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1198/jasa.2011.tm09779 |
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