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MODEL-FREE FORWARD SCREENING VIA CUMULATIVE DIVERGENCE
Feature screening plays an important role in the analysis of ultrahigh dimensional data. Due to complicated model structure and high noise level, existing screening methods often suffer from model misspecification and the presence of outliers. To address these issues, we introduce a new metric named...
Enregistré dans:
| Publié dans: | J Am Stat Assoc |
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| Auteurs principaux: | , , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
2019
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7821979/ https://ncbi.nlm.nih.gov/pubmed/33487782 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2019.1632078 |
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