Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/49365
Authors: 
Neumeyer, Natalie
Dette, Holger
Nagel, Eva-Renate
Year of Publication: 
2003
Series/Report no.: 
Technical Report // Universität Dortmund, SFB 475 Komplexitätsreduktion in Multivariaten Datenstrukturen 2003,25
Abstract: 
In the classical linear regression model the problem of testing for symmetry of the error distribution is considered. The test statistic is a functional of the difference between the two empirical distribution functions of the estimated residuals and their counterparts with opposite signs. The weak convergence of the difference process to a Gaussian process is established. 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.
Subjects: 
M-estimation
goodness-of-fit tests
testing for symmetry
empirical process of residuals
linear model
Document Type: 
Working Paper

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