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Confidence Intervals for Sparse Penalized Regression with Random Designs
With the abundance of large data, sparse penalized regression techniques are commonly used in data analysis due to the advantage of simultaneous variable selection and estimation. A number of convex as well as non-convex penalties have been proposed in the literature to achieve sparse estimates. Des...
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| Izdano u: | J Am Stat Assoc |
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| Glavni autori: | , , , |
| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
2019
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| Teme: | |
| Online pristup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7716883/ https://ncbi.nlm.nih.gov/pubmed/33281249 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2019.1585251 |
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