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

Philipp Sibbertsen

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.

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Year of publication:	1998
Authors:	Sibbertsen, Philipp
Publisher:	Dortmund : SFB 475, Universität Dortmund
Subject:	Linear regression model \| long - range dependence \| robustness \| Schätztheorie \| Estimation theory \| Regressionsanalyse \| Regression analysis \| Robustes Verfahren \| Robust statistics