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Activity Number:
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498
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Type:
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Invited
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Date/Time:
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Thursday, August 7, 2008 : 10:30 AM to 12:20 PM
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Sponsor:
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WNAR
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| Abstract - #300390 |
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Title:
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Variable Selection for High-Dimensional Correlated Data
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Author(s):
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Xihong Lin*+
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Companies:
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Harvard University
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Address:
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Department of Biostatistics, Boston, MA, 02115,
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Keywords:
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Variable selection ; Penalized Likelihood ; Correlated data ; Sparseness ; Asymptotics ; High-dimensional data
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Abstract:
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We propose several variable selection methods for correlated data, such as longitudinal and clustered data, based on regularized likelihood functions. We study the theoretical properties of these methods, and compare their theoretical performance. Their finite sample performance is evaluated using simulation studies and illustrated using a data example.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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