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