S-estimation in the nonlinear regression model with long-memory error terms
AbstractIn 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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Bibliographic InfoPaper provided by Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen in its series Technical Reports with number 1999,36.
Date of creation: 1999
Date of revision:
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Nonlinear regression model; long - range dependence; robustness;
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- Sakata, Shinichi & White, Halbert, 2001. "S-estimation of nonlinear regression models with dependent and heterogeneous observations," Journal of Econometrics, Elsevier, Elsevier, vol. 103(1-2), pages 5-72, July.
- Arie Preminger & Shinichi Sakata, 2007.
"A model selection method for S-estimation,"
Econometrics Journal, Royal Economic Society,
Royal Economic Society, vol. 10(2), pages 294-319, 07.
- PREMINGER, Arie & SAKATA, Shinichi, 2005. "A model selection method for S-estimation," CORE Discussion Papers, UniversitÃ© catholique de Louvain, Center for Operations Research and Econometrics (CORE) 2005073, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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