Authors: Dette, Holger
Neumeyer, Natalie
Title: Testing for Symmetric Error Distribution in Nonparametric Regression Models
Language (ISO): en
Abstract: 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.
Subject Headings: empirical process of residuals
testing for symmetry
nonparametric regression
URI: http://hdl.handle.net/2003/4973
http://dx.doi.org/10.17877/DE290R-15099
Issue Date: 2003
Publisher: Universitätsbibliothek Dortmund
Appears in Collections:Sonderforschungsbereich (SFB) 475

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