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Comparing nonparametric versus parametric regression fits

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  • HARDLE, W.
  • MAMMEN, E.

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  • Hardle, W. & Mammen, E., 1990. "Comparing nonparametric versus parametric regression fits," CORE Discussion Papers 1990065, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Handle: RePEc:cor:louvco:1990065
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    References listed on IDEAS

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    1. Hardle, Wolfgang & Linton, Oliver, 1986. "Applied nonparametric methods," Handbook of Econometrics,in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 38, pages 2295-2339 Elsevier.
    2. Collomb, Gérard & Härdle, Wolfgang, 1986. "Strong uniform convergence rates in robust nonparametric time series analysis and prediction: Kernel regression estimation from dependent observations," Stochastic Processes and their Applications, Elsevier, vol. 23(1), pages 77-89, October.
    3. Hã„Rdle, W. & Marron, S.J., 1990. "Semiparametric comparison of regression curves," CORE Discussion Papers RP 890, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Konakov, V. D. & Piterbarg, V. I., 1984. "On the convergence rate of maximal deviation distribution for kernel regression estimates," Journal of Multivariate Analysis, Elsevier, vol. 15(3), pages 279-294, December.
    5. Dennis Cox & Eunmee Koh, 1989. "A smoothing spline based test of model adequacy in polynomial regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 41(2), pages 383-400, June.
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