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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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| Publicat a: | J Am Stat Assoc |
|---|---|
| Autors principals: | , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2016
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| Matèries: | |
| Accés en línia: | 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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