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 ANTAC: 
Asymptotic normal estimation of covariate-adjusted gaussian graphical model.

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We proposed a tuning-free procedure 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. We further apply the asymptotic normality result to perform support recovery through edge-wise adaptive thresholding. This support recovery procedure is called ANTAC, standing for Asymptotically Normal estimation with Thresholding after Adjusting Covariates. ANTAC is implemented as an R package. 

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Chen Group

Section of Genetic Medicine
​University of Chicago​
5841 S. Maryland Ave N417A
Chicago, IL 60637 USA
Tel: 773-834-3175 
Email: [email protected]

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