JSM 2013 Home
Online Program Home
My Program

Abstract Details

Activity Number: 73
Type: Topic Contributed
Date/Time: Sunday, August 4, 2013 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistical Learning and Data Mining
Abstract - #310130
Title: Sparse Laplacian Shrinkage for Inverse Covariance Estimation in Heterogeneous Sample
Author(s): Takumi Saegusa*+ and Ali Shojaie
Companies: University of Washington and University of Washington
Keywords: graphical model ; high dimensional ; graph Laplacian ; covariance matrix ; network ; alternating directions method of multipliers
Abstract:

We consider the problem of estimating multiple Gaussian graphical models from heterogeneous samples where the relationship among samples is given as a graph. This problem is motivated by estimation of gene networks for cancer patients with multiple subtypes, some of which are similar to each other but others of which are not. Estimation of a single graphical model in this problem blurs heterogeneity across samples while previously proposed methods in a similar problem often assume the equal level of resemblance among samples, resulting in inefficient (and misleading in some cases) use of information. We propose a method to jointly estimate multiple graphical models by borrowing strength across samples in estimating a common structure and exploiting resemblance information among samples given as a graph to make contrasts. This is achieved by combined use of the ell-1 penalty for the former and the graph Laplacian shrinkage penalty for the latter. We implement an ADMM algorithm to compute our estimator and illustrate its performance through simulations and real data sets.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2013 program




2013 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

ASA Meetings Department  •  732 North Washington Street, Alexandria, VA 22314  •  (703) 684-1221  •  meetings@amstat.org
Copyright © American Statistical Association.