Arbeitspapier
Testing for symmetric error distribution in nonparametric regression models
For the problem of testing symmetry of the error distribution in a nonparametric regression model we propose as a test statistic the difference between the two empirical distribution functions of estimated residuals and their counterparts with opposite signs. The weak convergence of the difference process to a Gaussian process is shown. The covariance structure of this process depends heavily on the density of the error distribution, and for this reason the performance of a symmetric wild bootstrap procedure is discussed in asymptotic theory and by means of a simulation study. In contrast to the available procedures the new test is also applicable under heteroscedasticity.
- Language
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Englisch
- Bibliographic citation
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Series: Technical Report ; No. 2003,11
- Subject
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empirical process of residuals
testing for symmetry
nonparametric regression
Regression
Nichtparametrisches Verfahren
Statistischer Test
Theorie
- Event
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Geistige Schöpfung
- (who)
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Neumeyer, Natalie
Dette, Holger
- Event
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Veröffentlichung
- (who)
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Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
- (where)
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Dortmund
- (when)
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2003
- Handle
- Last update
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10.03.2025, 11:41 AM CET
Data provider
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Object type
- Arbeitspapier
Associated
- Neumeyer, Natalie
- Dette, Holger
- Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
Time of origin
- 2003