S-estimators in the linear regression model with long-memory error terms

Philipp Sibbertsen

No 1998,33, Technical Reports from Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen

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.

Keywords: Linear regression model; long - range dependence; robustness (search for similar items in EconPapers)
Date: 1998
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb475:199833

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