Abstract Details
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Activity Number:
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422
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Type:
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Contributed
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Date/Time:
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Tuesday, August 6, 2013 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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| Abstract - #307992 |
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Title:
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Optimal Estimation for the Functional Cox Model
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Author(s):
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Simeng Qu*+ and Xiao Wang
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Companies:
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Purdue University and Purdue University
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Keywords:
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functional data ;
Cox model ;
partial likelihood ;
right-censored data ;
reproducing kernel Hilbert space ;
rate of convergence
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Abstract:
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This paper studies the functional linear Cox model, in which the covariate is a functional. The coefficient function is assumed to be in a reproducing kernel Hilbert space. An easily implementable roughness regularization method is used to obtain the estimate. Asymptotic properties of the maximum partial likelihood estimate with right-censored data are established. It is shown that this estimate achieves the optimal rate of convergence. Simulation studies are carried out to illustrate the merit of the estimate.
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Authors who are presenting talks have a * after their name.
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