This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
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Activity Number:
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403
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 3, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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| Abstract - #309156 |
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Title:
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Nonparametric Covariate Adjustment in Conditional Copulas: An Application to Twin Birth Weights
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Author(s):
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Elif Fidan Acar*+ and Radu Craiu and Fang Yao
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Companies:
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University of Toronto and University of Toronto and University of Toronto
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Address:
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100 St. George St. 6th floor, Toronto, ON, M5S 3G3, Canada
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Keywords:
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Copula parameter ;
Copula selection ;
Covariate effect ;
Local likelihood
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Abstract:
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We study nonparametric estimation and inference for the copula parameter in conditional copulas. Our interest is to characterize the covariate effects on the strength of dependence when modeling the joint behavior of two or more random variables. Using local polynomial techniques we propose a nonparametric estimation procedure for the functional relationship between the copula parameter and the covariate. Our second contribution is to introduce a novel copula selection method based on cross-validated prediction errors. We apply our techniques to a subset of the United States Matched Multiple Birth Data Set and observe that level of dependence between the birth weights of twins varies with the gestation age in a nonlinear pattern.
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