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Abstract Details
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Activity Number:
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274
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Type:
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Invited
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Date/Time:
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Tuesday, August 2, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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International Indian Statistical Association
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| Abstract - #300207 |
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Title:
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Mixture Models and High-Dimensional Data
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Author(s):
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Soumendra Nath Lahiri*+ and Subhodeep Mukhopadhyay
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Companies:
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Texas A & M University and Texas A & M University
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Address:
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Department of Statistics; MS 3143, College Station , 77843,
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Keywords:
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High dimensional data ;
Mixture models ;
optimal classifier
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Abstract:
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In this talk, we consider Gaussian mixture models in high dimensional set up where the dimension of the observations diverges with the sample size. We derive asymptotic properties of the optimal classifier based on mixture models and illustrate the results with applications to Gene expression data.
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Authors who are presenting talks have a * after their name.
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