The M-estimation in a multi-phase random nonlinear model
This paper extends the results of M-estimation in [Koul, H.L., Qian, L., Surgailis, D., 2003. Asymptotics of M-estimators in two-phase linear regression models. Stochastic Processes and their Applications, 103, 123-154] to a general nonlinear random design regression model with multiple change-points at unknown times. The M-estimator of locations of breaks and of regression parameters are consistent. Convergence rate and asymptotic distribution are obtained.
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Volume (Year): 79 (2009)
Issue (Month): 5 (March)
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References listed on IDEAS
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- Ciuperca Gabriela, 2004. "Maximum likelihood estimator in a two-phase nonlinear random regression model," Statistics & Risk Modeling, De Gruyter, vol. 22(4/2004), pages 335-349, April.
- Perron, P. & Bai, J., 1995.
"Estimating and Testing Linear Models with Multiple Structural Changes,"
Cahiers de recherche
9552, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
- Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche 9552, Universite de Montreal, Departement de sciences economiques.
- Koul, Hira L. & Qian, Lianfen & Surgailis, Donatas, 2003. "Asymptotics of M-estimators in two-phase linear regression models," Stochastic Processes and their Applications, Elsevier, vol. 103(1), pages 123-154, January.
- Lai, T. L. & Robbins, Herbert & Wei, C. Z., 1979. "Strong consistency of least squares estimates in multiple regression II," Journal of Multivariate Analysis, Elsevier, vol. 9(3), pages 343-361, September.
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