Abstract #300233

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JSM 2003 Abstract #300233
Activity Number: 210
Type: Contributed
Date/Time: Tuesday, August 5, 2003 : 8:30 AM to 10:20 AM
Sponsor: Section on Nonparametric Statistics
Abstract - #300233
Title: A Lack-of-Fit Test for Heteroscedastic Regression Models via Cosine-Series Smoothers
Author(s): Chin-Shang Li*+
Companies: St. Jude Children's Research Hospital
Address: Department of Biostatistics, Memphis, TN, 38105-2729,
Keywords: fit-comparison test ; order selection ; quasi-likelihood estimator ; cosine-series smoother
Abstract:

A test is derived to assess the validity of heteroscedastic nonlinear regression models by using a nonparametric cosine regression methodology. For order selection, we propose a data-driven method that uses the parametric null model optimal order. This method yields a test that is asymptotically normally distributed under the null hypothesis and is consistent against any fixed alternative. Simulation studies that test the lack of fit of a generalized linear model are conducted to compare the performance of the proposed test with that of an existing nonparametric kernel test. A dataset of esterase levels is used to demonstrate the proposed methodology in practice.

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