Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/77161 
Year of Publication: 
1998
Series/Report no.: 
Technical Report No. 1998,33
Publisher: 
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen, Dortmund
Abstract: 
We investigate the behaviour of S - estimators in the linear regression model, when the error terms are long-memory Gaussian processes. It turns out that under mild regularity conditions S - estimators are still normally distributed with a similar variance - covariance structure as in the i.i.d - case. This assertion holds for the parameter estimates as well as for the scale estimates. Also the rate of convergence is for S - estimators the same as for the least squares estimator and for the BLUE.
Subjects: 
Linear regression model
long - range dependence
robustness
Document Type: 
Working Paper

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