Comparing nonparametric versus parametric regression fits
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Bibliographic InfoPaper provided by Humboldt Universitaet Berlin in its series Statistic und Oekonometrie with number 9205.
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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).
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hardle, W., 1992.
"Applied Nonparametric Methods,"
9204, Catholique de Louvain - Institut de statistique.
- Wolfgang Hardle & Oliver Linton, 1994. "Applied Nonparametric Methods," Cowles Foundation Discussion Papers 1069, Cowles Foundation for Research in Economics, Yale University.
- Hardle, W., 1992. "Applied Nonparametric Methods," Discussion Paper 1992-6, Tilburg University, Center for Economic Research.
- HÄRDLE, Wolfgang, 1992. "Applied nonparametric methods," CORE Discussion Papers 1992003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Hardle, W., 1992. "Applied Nonparametric Methods," Papers 9206, Tilburg - Center for Economic Research.
- Oliver LINTON, .
"Applied nonparametric methods,"
Statistic und Oekonometrie
9312, Humboldt Universitaet Berlin.
- Dennis Cox & Eunmee Koh, 1989. "A smoothing spline based test of model adequacy in polynomial regression," Annals of the Institute of Statistical Mathematics, Springer, vol. 41(2), pages 383-400, June.
- Härdle, W. & Marron, S.J., .
"Semiparametric comparison of regression curves,"
CORE Discussion Papers RP
-890, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Azzalini,A. & Bowman,A.W. & Haerdle,W., 1988. "On the use of nonparametric regression for model checking," Discussion Paper Serie A 195, University of Bonn, Germany.
- 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.
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