[Statlist] Next talk: March 26, 2010 with Cun-Hui Zhang, Rutgers University U.S.A.

[Susanne Kaiser-Heinzmann]

ETH and University of Zurich

Proff. A.D. Barbour - P. Buehlmann -  L. Held -
H.R. Kuensch - M. Maathuis - W. Stahel - S. van de Geer


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We are glad to announce the following talk

*Friday, March 26, 2010 15.15 - 16.15  HG  G 19.1 *
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with Cun-Hui Zhang, Rutgers University, U.S.A

Title:

GRAPHICAL MODEL SELECTION AND STATISTICAL INFERENCE ABOUT LARGE INVERSE 
MATRICES

Abstract:

We propose a new method of learning a large symmetric target matrix 
whose inverse can
be directly approximated by data. Our primary example of the target 
matrix is the inverse
of a population correlation or covariance matrix. The proposed method, 
called GMACS,
naturally leads to a uniform error bound which can be viewed as 
simultaneous con
dence
intervals for the elements of the target matrix from an oracle expert. 
Since the uniform
error bound essentially turns a statistical experiment with indirect 
observations into one
with direct observations, conservative solutions follow for a number of 
hypothesis testing
and structure estimation problems, including graphical model selection 
and consistent esti-
mation of the target under the spectrum and other norms. Our main ideas 
and results are
applicable to general symmetric data and target matrices.

This abstract is also to be found under the following link:
http://stat.ethz.ch/talks/research_seminar

-- 
ETH Zürich
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Seminar für Statistik
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