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Multivariate bandwidth selection for local linear regression

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  • L. Yang
  • R. Tschernig

Abstract

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Suggested Citation

  • L. Yang & R. Tschernig, 1999. "Multivariate bandwidth selection for local linear regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(4), pages 793-815.
  • Handle: RePEc:bla:jorssb:v:61:y:1999:i:4:p:793-815
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    Citations

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    Cited by:

    1. Rolf Tschernig & Lijian Yang, 2000. "Nonparametric Estimation of Generalized Impulse Response Functions," Econometric Society World Congress 2000 Contributed Papers 1417, Econometric Society.
    2. Gilboa, Itzhak & Lieberman, Offer & Schmeidler, David, 2011. "A similarity-based approach to prediction," Journal of Econometrics, Elsevier, vol. 162(1), pages 124-131, May.
    3. Giordano, Francesco & Parrella, Maria Lucia, 2016. "Bias-corrected inference for multivariate nonparametric regression: Model selection and oracle property," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 71-93.
    4. Max Köhler & Anja Schindler & Stefan Sperlich, 2014. "A Review and Comparison of Bandwidth Selection Methods for Kernel Regression," International Statistical Review, International Statistical Institute, vol. 82(2), pages 243-274, August.
    5. Mohamed Chikhi & Claude Diebolt, 2010. "Nonparametric analysis of financial time series by the Kernel methodology," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(5), pages 865-880, August.
    6. Hupfeld, Stefan, 2009. "Rich and healthy--better than poor and sick?: An empirical analysis of income, health, and the duration of the pension benefit spell," Journal of Health Economics, Elsevier, vol. 28(2), pages 427-443, March.
    7. Gonzalez Manteiga, W. & Martinez Miranda, M. D. & Perez Gonzalez, A., 2004. "The choice of smoothing parameter in nonparametric regression through Wild Bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 47(3), pages 487-515, October.
    8. CHIKHI, Mohamed, 2009. "Identification non paramétrique d’un processus non linéaire hétéroscédastique
      [Nonparametric identification of heteroscedastic nonlinear process]
      ," MPRA Paper 82108, University Library of Munich, Germany, revised 2009.
    9. CHIKHI, Mohamed, 2017. "Chocs exogènes et non linéarités dans les séries boursières: Application à la modélisation non paramétrique du cours de l'action Orange
      [Exogenous Shocks and nonlinearity in the stock exchange seri
      ," MPRA Paper 76691, University Library of Munich, Germany, revised 2017.
    10. Yang, Lijian, 2006. "A semiparametric GARCH model for foreign exchange volatility," Journal of Econometrics, Elsevier, vol. 130(2), pages 365-384, February.
    11. Yingcun Xia & Howell Tong & W. K. Li & Li-Xing Zhu, 2002. "An adaptive estimation of dimension reduction space," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 363-410.
    12. Chikhi, Mohamed & Terraza, Michel, 2002. "Un essai de prévision non paramétrique de l'action France Télécom
      [A nonparametric prediction test of the France Telecom stock proces]
      ," MPRA Paper 77268, University Library of Munich, Germany, revised Dec 2003.
    13. Andrews, Donald W.K. & Shi, Xiaoxia, 2014. "Nonparametric inference based on conditional moment inequalities," Journal of Econometrics, Elsevier, vol. 179(1), pages 31-45.
    14. Vidaurre, Diego & Bielza, Concha & Larrañaga, Pedro, 2013. "Sparse regularized local regression," Computational Statistics & Data Analysis, Elsevier, vol. 62(C), pages 122-135.
    15. Naito, Kanta & Yoshizaki, Masahiro, 2009. "Bandwidth selection for a data sharpening estimator in nonparametric regression," Journal of Multivariate Analysis, Elsevier, vol. 100(7), pages 1465-1486, August.
    16. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, number 8355.
    17. Wolfgang Härdle & Torsten Kleinow & Rolf Tschernig, 2001. "Web Quantlets for Time Series Analysis," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(1), pages 179-188, March.
    18. Qiu, D. & Shao, Q. & Yang, L., 2013. "Efficient inference for autoregressive coefficients in the presence of trends," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 40-53.
    19. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871.
    20. repec:spr:compst:v:32:y:2017:i:3:d:10.1007_s00180-017-0709-3 is not listed on IDEAS
    21. Biqing Cai & Dag Tjøstheim, 2015. "Nonparametric Regression Estimation for Multivariate Null Recurrent Processes," Econometrics, MDPI, Open Access Journal, vol. 3(2), pages 1-24, April.
    22. Chevallier, Julien, 2011. "Nonparametric modeling of carbon prices," Energy Economics, Elsevier, vol. 33(6), pages 1267-1282.
    23. Cheng, Ming-Yen & Peng, Liang, 2006. "Simple and efficient improvements of multivariate local linear regression," Journal of Multivariate Analysis, Elsevier, vol. 97(7), pages 1501-1524, August.
    24. Francesco Giordano & Maria Lucia Parrella, 2014. "Bias-corrected inference for multivariate nonparametric regression: model selection and oracle property," Working Papers 3_232, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno.

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