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Sparsistency and Rates of Convergence in Large Covariance Matrix Estimation
This paper studies the sparsistency and rates of convergence for estimating sparse covariance and precision matrices based on penalized likelihood with nonconvex penalty functions. Here, sparsistency refers to the property that all parameters that are zero are actually estimated as zero with probabi...
Tallennettuna:
| Päätekijät: | , |
|---|---|
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
2009
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2995610/ https://ncbi.nlm.nih.gov/pubmed/21132082 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1214/09-AOS720 |
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