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Selection Consistency of Lasso-Based Procedures for Misspecified High-Dimensional Binary Model and Random Regressors
We consider selection of random predictors for a high-dimensional regression problem with a binary response for a general loss function. An important special case is when the binary model is semi-parametric and the response function is misspecified under a parametric model fit. When the true respons...
Guardat en:
| Publicat a: | Entropy (Basel) |
|---|---|
| Autors principals: | , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
MDPI
2020
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7516565/ https://ncbi.nlm.nih.gov/pubmed/33285928 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e22020153 |
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