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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...

Deskribapen osoa

Gorde:
Xehetasun bibliografikoak
Egile Nagusiak: Fan, Jianqing, Feng, Yang, Song, Rui
Formatua: Artigo
Hizkuntza:Inglês
Argitaratua: 2011
Gaiak:
Sarrera elektronikoa: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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