Abstract Details
Activity Number:
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528
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 12, 2015 : 10:30 AM to 12:20 PM
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Sponsor:
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International Indian Statistical Association
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Abstract #317506
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Title:
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Estimation and Variable Selection in High-Dimensional Linear Mixed Models
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Author(s):
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Abhishek Kaul* and Akshita Chawla and Tapabrata Maiti
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Companies:
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Michigan State University and Michigan State University and Michigan State University
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Keywords:
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High Dimension ;
Linear Mixed Models ;
Variable selection
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Abstract:
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We propose a new method to select and estimate the co-variance components of the random effects for linear mixed models where both the fixed effects and random effects can be high dimensional. We establish the associated statistical error bounds for the proposed estimation procedure while also providing variable selection properties. The finite sample results are also investigated via a simulation study. Finally we apply the proposed estimation procedure to a real data set.
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Authors who are presenting talks have a * after their name.
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