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Abstract Details
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Activity Number:
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489
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Type:
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Invited
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Date/Time:
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Wednesday, August 3, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Nonparametric Statistics
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| Abstract - #300236 |
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Title:
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Nonparametric Regression with Continuous and Categorical Predictors
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Author(s):
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Jean Opsomer*+ and Jay Breidt and Ismael Sanchez
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Companies:
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Colorado State University and Colorado State University and University of Granada
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Address:
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, , CO, 80523,
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Keywords:
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kernel regression ;
small area estimation
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Abstract:
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We will consider the problem of fitting a nonparametric regression model for the case of a continuous dependent variable and a mixture of continuous, ordinal and nominal independent variables. We will use generalized product kernel regression, which combines kernels appropriate for all three types of covariates. Some asymptotic theory for the ordinal variable kernel regression will be developed and applied to this scenario. This work is motivated by a small area estimation problem of the U.S. Bureau of Labor Statistics, who are interested in estimating the mean wage by job type, job level and geographic area based on data from the National Compensation Survey.
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