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Activity Number: 418
Type: Topic Contributed
Date/Time: Tuesday, August 2, 2016 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract #318846 View Presentation
Title: Sure Screening for Transelliptical Graphical Models
Author(s): Yuxiang Xie* and Chengchun Shi and Rui Song and Daniela Witten
Companies: University of Washington and North Carolina State University and North Carolina State University and University of Washington
Keywords: High Dimensionality ; Kendall's tau ; Partial Correlation ; Sparsity ; Undirected Graph
Abstract:

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.


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