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We propose a sure screening approach for recovering the structure of atranselliptical graphical model in the high dimensional setting. We estimatethe partial correlation graph by thresholding the elements of an estimator ofthe sample correlation matrix obtained using Kendall's tau statistic. Under asimple assumption on the relationship between the correlation and partialcorrelation graphs, we show that with high probability, the estimated edge setcontains the true edge set, and the size of the estimated edge set iscontrolled. We develop a threshold value that allows for control of theexpected false positive rate. In simulation and on an equities data set, weshow that transelliptical graphical sure screening performs quite competitivelywith more computationally demanding techniques for graph estimation.

Sure Screening for Transelliptical Graphical Models