Activity Number:
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254
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Type:
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Contributed
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Date/Time:
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Tuesday, August 13, 2002 : 2:00 PM to 3:50 PM
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Sponsor:
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General Methodology
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Abstract - #301047 |
Title:
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A Lack of Fit Test for Heteroscedastic Regression Models via Series--Type Smoothers
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Author(s):
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Chin-Shang Li*+
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Affiliation(s):
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St. Jude Children's Research Hospital
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Address:
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332 North Lauderdale St., Memphis, Tennessee, 38105, USA
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Keywords:
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fit comparison test ; order selection ; quasi-likelihood estimator ; series smoother
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Abstract:
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A test is derived to assess the validity of heteroscedastic nonlinear regression models by using a nonparametric series-type regression methodology. A data-driven method is proposed that uses the parametric null model optimal order for order selection, yielding a test that is asymptotically normally distributed under the null hypothesis and is consistent against any fixed alternative. The resulting test is applied to the problem of testing the lack of fit of a generalized linear model.
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