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
Englisch

Bibliographic citation
Series: Technical Report ; No. 2003,11

Subject
empirical process of residuals
testing for symmetry
nonparametric regression
Regression
Nichtparametrisches Verfahren
Statistischer Test
Theorie

Event
Geistige Schöpfung
(who)
Neumeyer, Natalie
Dette, Holger
Event
Veröffentlichung
(who)
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
(where)
Dortmund
(when)
2003

Handle
Last update
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

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