Abstract Details
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Activity Number:
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148
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Type:
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Invited
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Date/Time:
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Monday, August 5, 2013 : 10:30 AM to 12:20 PM
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Sponsor:
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SSC
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| Abstract - #307311 |
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Title:
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Regularization on Multivariate Functional-Coefficient Regression Models
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Author(s):
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Jiancheng Jiang*+
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Companies:
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The University of North Carolina at Charlotte
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Keywords:
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Local linear smoothing ;
Vector time series ;
regularization ;
Spatial Quantile regression
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Abstract:
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In this talk I introduce a multivariate functional-coefficient regression model to fit vector time series data. A ``penalized local spatial quantile regression" (PLSQR) method is proposed to estimate the unknown coefficient matrices. To achieve efficiency and robustness, we propose a "weighted composite PLSQR" (WCPLSQR) estimation approach. Selection consistency and some oracle properties are established. Choice of weights and bandwidth selection are also considered. Simulations and a real example are used to evaluate the performance of the proposed estimators.
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Authors who are presenting talks have a * after their name.
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