Average squared residuals approach for testing linear hypotheses in nonparametric regression
Authors:
Zaher Mohdeb a;
Abdelkader Mokkadem b
| Affiliations: | a Department of Mathematics, University Mentouri, Constantine, Algeria |
b Department of Mathematics, University of Versailles-St-Quentin B timent Fermat, Versailles Cedex, France |
DOI:
10.1080/10485250310001640145
Publication Frequency:
8 issues per year
Published in:
Journal of Nonparametric Statistics,
Volume
16,
Issue
1 &
2
February
2004
, pages 3
- 12
Subjects:
Mathematical Economics;
Mathematical Finance;
Medical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
Number of References: 15
Formats available:
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(English)
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Abstract
We construct linear hypotheses tests for the regression function in nonparametric regression model in the case of a homoscedastic error structure and a fixed design. The test statistic we use is based on the average of squared residuals. We show the asymptotic normality of this statistic under the null hypothesis and the alternative. The work also contains a simulation study to investigate the finite sample behavior of the proposed test.
|
| Keywords: Nonlinear regression; Nonparametric test |
| view references (15) |

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timent Fermat, Versailles Cedex, France
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