Authors: | Dette, Holger Van Keilegom, Ingrid |
Title: | A new test for the parametric form of the variance function in nonparametric regression |
Language (ISO): | en |
Abstract: | In the common nonparametric regression model the problem of testing for the parametric form of the conditional variance is considered. A stochastic process based on the difference between the empirical processes obtained from the standardized nonparametric residuals under the null hypothesis (of a specific parametric form of the variance function) and the alternative is introduced and its weak convergence established. This result is used for the construction of a Cramér von Mises type statistic for testing the parametric form of the conditional variance. The finite sample properties of a bootstrap version of this test are investigated by means of a simulation study. In particular the new procedure is compared with some of the currently available methods for this problem and its performance is illustrated by means of a data example. |
Subject Headings: | Bootstrap Kernel estimation Nonparametric regression Residual distribution Testing heteroscedasticity Testing homoscedasticity |
URI: | http://hdl.handle.net/2003/21636 http://dx.doi.org/10.17877/DE290R-14489 |
Issue Date: | 2005-10-11T14:37:10Z |
Appears in Collections: | Sonderforschungsbereich (SFB) 475 |
Files in This Item:
File | Description | Size | Format | |
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tr32-05.pdf | DNB | 202.8 kB | Adobe PDF | View/Open |
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