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Activity Number: 528
Type: Topic Contributed
Date/Time: Wednesday, August 12, 2015 : 10:30 AM to 12:20 PM
Sponsor: International Indian Statistical Association
Abstract #317506
Title: Estimation and Variable Selection in High-Dimensional Linear Mixed Models
Author(s): Abhishek Kaul* and Akshita Chawla and Tapabrata Maiti
Companies: Michigan State University and Michigan State University and Michigan State University
Keywords: High Dimension ; Linear Mixed Models ; Variable selection
Abstract:

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.


Authors who are presenting talks have a * after their name.

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