This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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297
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Type:
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Contributed
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Date/Time:
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Tuesday, August 3, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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Abstract - #308228 |
Title:
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Nonlinear Varying Coefficient Models
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Author(s):
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Esra Kurum*+ and Yang (Rick) Wang and Runze Li and Damla Senturk
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Companies:
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Penn State and Freddie Mac and Penn State and Penn State
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Address:
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200 Highland Ave. #303, State College, PA, 16801,
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Keywords:
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Asymptotic normality ;
Generalized Likelihood Tests ;
Local linear regression ;
Nonlinear regression model
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Abstract:
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We extend varying coefficient models to nonlinear varying coefficient models, where the relationship between the predictors and the response variable is allowed to be nonlinear. We propose a local linear estimation technique for nonlinear varying coefficient models. Since there is no closed form for the resulting estimates in a nonlinear regression model, we propose additional Taylor's expansions to address the computational challenges arising in optimization. We establish asymptotic normality of the proposed estimators leading to point-wise asymptotic confidence bands for the targeted varying coefficient functions. An extension of the generalized likelihood ratio-type test is also proposed for testing whether the coefficient functions vary over a covariate. An application to an empirical ecological study and simulation studies are given to show the efficacy of the proposed method.
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