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Variable Selection and Regularization in Quantile Regression via Minimum Covariance Determinant Based Weights
The importance of variable selection and regularization procedures in multiple regression analysis cannot be overemphasized. These procedures are adversely affected by predictor space data aberrations as well as outliers in the response space. To counter the latter, robust statistical procedures suc...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7823782/ https://www.ncbi.nlm.nih.gov/pubmed/33383623 http://dx.doi.org/10.3390/e23010033 |