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Non-Concave Penalized Likelihood with NP-Dimensionality
Penalized likelihood methods are fundamental to ultra-high dimensional variable selection. How high dimensionality such methods can handle remains largely unknown. In this paper, we show that in the context of generalized linear models, such methods possess model selection consistency with oracle pr...
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| Main Authors: | , |
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| Format: | Artigo |
| Language: | Inglês |
| Published: |
2011
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| Subjects: | |
| Online Access: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3266747/ https://ncbi.nlm.nih.gov/pubmed/22287795 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TIT.2011.2158486 |
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