Dette, HolgerNagel, Eva-RenateNeumeyer, Natalie2004-12-062004-12-062003http://hdl.handle.net/2003/498710.17877/DE290R-15048In 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.enUniversitätsbibliothek DortmundM-estimationgoodness-of-fit teststesting for symmetryempirical process of residualslinear model310A Note on Testing Symmetry of the Error Distribution in Linear Regression Modelsreport