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S-estimation in the nonlinear regression model with long-memory error terms

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  • Sibbertsen, Philipp

Abstract

In this paper we consider the asymptotic distribution of S -estimators in the nonlinear regression model with long-memory error terms. S - estimators are robust estimates with a high breakdown point and good asymptotic properties in the i.i.d case. They are constructed for linear regression. In the nonlinear regression model with long-memory errors it turns out. that S-estimators are asymptotically normal with a rate of convergence of n1-h , ½

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File URL: http://econstor.eu/bitstream/10419/77362/2/1999-36.pdf
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Bibliographic Info

Paper provided by Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen in its series Technical Reports with number 1999,36.

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Date of creation: 1999
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Handle: RePEc:zbw:sfb475:199936

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Related research

Keywords: Nonlinear regression model; long - range dependence; robustness;

References

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  1. Sakata, Shinichi & White, Halbert, 2001. "S-estimation of nonlinear regression models with dependent and heterogeneous observations," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 5-72, July.
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Cited by:
  1. Arie Preminger & Shinichi Sakata, 2007. "A model selection method for S-estimation," Econometrics Journal, Royal Economic Society, vol. 10(2), pages 294-319, 07.

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