How Sensitive Are Average Derivatives

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Authors	:	Hardle, W. Tsybakov, AB.
Document type	:	Article de périodique (Journal article) – Article de recherche
Abstract	:	Average derivatives are the mean slopes of regression functions. In practice they are estimated via a nonparametric smoothing technique. Every smoothing method needs a calibration parameter that determines the finite sample performance. In this paper we use the kernel estimation method and develop a formula for the bandwidth that describes the sensitivity of the average derivative estimator. One can determine an optimal smoothing parameter from this formula which tries out to undersmooth the density of the regression variable.
Access type	:	Accès restreint
Publication date	:	1993
Language	:	Anglais
Journal information	:	"Journal of Econometrics" - Vol. 58, no. 1-2, p. 31-48 (1993)
Peer reviewed	:	yes
Publisher	:	Elsevier Science Sa Lausanne (Lausanne 1)
issn	:	0304-4076
e-issn	:	1872-6895
Publication status	:	Publié
Affiliation	:	UCL
Links	:	[DOI]https://doi.org/10.1016/0304-4076(93)90112-I [Handle]http://hdl.handle.net/2078.1/49997

Bibliographic reference	Hardle, W. ; Tsybakov, AB.. How Sensitive Are Average Derivatives. In: Journal of Econometrics, Vol. 58, no. 1-2, p. 31-48 (1993)
Permanent URL	http://hdl.handle.net/2078.1/49997