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Department of Statistics, The Ohio State University
Statistics and Biostatistics Colloquium Series
Group Variable Selection via Hierarchical Lasso and Its Oracle
Property
Ji Zhu
Department of Statistics, University of Michigan
3:30PM - Thursday, April 19, 2007
Room 170, Eighteenth Avenue Bldg. (EA 170)
ABSTRACT
In many engineering and scientific applications, predictor variables are
grouped, for example, in biological applications where assayed genes or
proteins can be grouped by biological role. Common statistical analysis
methods such as ANOVA, factor analysis, and functional modeling with
partially ordered basis sets also exhibit natural variable groupings.
We develop a new variable selection method that respects the group
constraint. Our new method enjoys benefits that existing successful
methods do not have, while offering the potential for achieving
theoretical "oracle" properties.
Meet the speaker in Room 212 Cockins Hall at 4:30
p.m. Refreshments will be served.
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