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Asymptotically Normal and Efficient Estimation of Covariate-Adjusted Gaussian Graphical Model
A tuning-free procedure is proposed to estimate the covariate-adjusted Gaussian graphical model. For each finite subgraph, this estimator is asymptotically normal and efficient. As a consequence, a confidence interval can be obtained for each edge. The procedure enjoys easy implementation and effici...
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| Vydáno v: | J Am Stat Assoc |
|---|---|
| Hlavní autoři: | , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
2016
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4974017/ https://ncbi.nlm.nih.gov/pubmed/27499564 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2015.1010039 |
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