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Regularized Quantile Regression and Robust Feature Screening for Single Index Models
We propose both a penalized quantile regression and an independence screening procedure to identify important covariates and to exclude unimportant ones for a general class of ultrahigh dimensional single-index models, in which the conditional distribution of the response depends on the covariates v...
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| Publicat a: | Stat Sin |
|---|---|
| Autors principals: | , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2016
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4771381/ https://ncbi.nlm.nih.gov/pubmed/26941542 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.5705/ss.2014.049 |
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