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Variable Selection for Partially Linear Models with Measurement Errors1
This article focuses on variable selection for partially linear models when the covariates are measured with additive errors. We propose two classes of variable selection procedures, penalized least squares and penalized quantile regression, using the nonconvex penalized principle. The first procedu...
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| Main Authors: | , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2009
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2697854/ https://ncbi.nlm.nih.gov/pubmed/20046976 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1198/jasa.2009.0127 |
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