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Title: Genetic Architecture of Complex Diseases: Implications for Discovery, Prediction and Prevention

  • Speaker: Dr. Nilanjan Chatterjee, National Cancer Institute, Chief of Division of Cancer Epidemiology & Genetics, Biostatistics Branch
  • Date & Time: Friday, March, 21, 3:30-4:30 pm
  • Location: Duques Hall, Room 152 (2201 G Street NW, Washington, DC 20052)
  • Directions: Foggy Bottom-GWU Metro Stop on the Orange and Blue Lines. The campus map is at http://www.gwu.edu/explore/visitingcampus/campusmaps.
  • Sponsor: The George Washington University, Department of Statistics. See http://statistics.columbian.gwu.edu/ for a list of seminars.


High dimensional covariance matrix estimation has seen its wide applications in panel data models and factor analysis. While the sparsity assumption on the covariance matrix directly might be restrictive, it is more reasonable to be satisfied when common factors are controlled first. This so-called "conditional sparsity (given factors)" assumption enables us to estimate various covariance matrices with good rate of convergence. Some applications in portfolio allocation are also presented.