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R robustified additive nonparametric regression

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  • Tamine, Julien
  • Härdle, Wolfgang
  • Yang, Lijian

Abstract

Additive modelling is known to be useful for multivariate nonparametric regression as it reduces the complexity of problem to the level of univariate regression. This usefulness could be compromised if the data set was contaminated by outliers whose detection and removal are particularly difficult to achieve in high dimension. We propose an estimation procedure for the additive component of the regression function , less sensitive to possible outliers in the sample. Our procedure is based on marginal integration of conditional R-estimators. In addition to univariate rate of convergence and asymptotic distribution, we also obtain robustness results for our estimator. All of our results are valid for a broad class of ß mixing processes. Monte Carlo findings confirm the theoretical results in finite sample.

Suggested Citation

  • Tamine, Julien & Härdle, Wolfgang & Yang, Lijian, 2002. "R robustified additive nonparametric regression," SFB 373 Discussion Papers 2002,78, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  • Handle: RePEc:zbw:sfb373:200278
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    References listed on IDEAS

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    1. Yacine Aït-Sahalia & Andrew W. Lo, 1998. "Nonparametric Estimation of State-Price Densities Implicit in Financial Asset Prices," Journal of Finance, American Finance Association, vol. 53(2), pages 499-547, April.
    2. Cizek, P. & Hardle, W., 2006. "Robust estimation of dimension reduction space," Computational Statistics & Data Analysis, Elsevier, pages 545-555.
    3. Ait-Sahalia, Yacine & Lo, Andrew W., 2000. "Nonparametric risk management and implied risk aversion," Journal of Econometrics, Elsevier, pages 9-51.
    4. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643, December.
    5. Davidson, James, 1994. "Stochastic Limit Theory: An Introduction for Econometricians," OUP Catalogue, Oxford University Press, number 9780198774037.
    6. Matthias Fengler & Wolfgang Härdle & Christophe Villa, 2003. "The Dynamics of Implied Volatilities: A Common Principal Components Approach," Review of Derivatives Research, Springer, vol. 6(3), pages 179-202, October.
    7. Pavel Cizek & Wolfgang Karl Härdle & Rafal Weron, 2005. "Statistical Tools for Finance and Insurance," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0501.
    8. Michal Benko & Wolfgang Härdle, 2005. "Common Functional Implied Volatility Analysis," SFB 649 Discussion Papers SFB649DP2005-012, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. McDonald, James B. & Xu, Yexiao J., 1995. "A generalization of the beta distribution with applications," Journal of Econometrics, Elsevier, pages 427-428.
    10. Ait-Sahalia, Yacine & Lo, Andrew W., 2000. "Nonparametric risk management and implied risk aversion," Journal of Econometrics, Elsevier, pages 9-51.
    11. Shinichi Sakata & Halbert White, 1998. "High Breakdown Point Conditional Dispersion Estimation with Application to S&P 500 Daily Returns Volatility," Econometrica, Econometric Society, vol. 66(3), pages 529-568, May.
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