Arbeitspapier
A uniform central limit theorem and efficiency for deconvolution estimators
We estimate linear functionals in the classical deconvolution problem by kernel estimators. We obtain a uniform central limit theorem with square root n rate on the assumption that the smoothness of the functionals is larger than the ill-posedness of the problem, which is given by the polynomial decay rate of the characteristic function of the error. The limit distribution is a generalized Brownian bridge with a covariance structure that depends on the characteristic function of the error and on the functionals. The proposed estimators are optimal in the sense of semiparametric efficiency. The class of linear functionals is wide enough to incorporate the estimation of distribution functions. The proofs are based on smoothed empirical processes and mapping properties of the deconvolution operator.
- Sprache
-
Englisch
- Erschienen in
-
Series: SFB 649 Discussion Paper ; No. 2012-046
- Klassifikation
-
Wirtschaft
Semiparametric and Nonparametric Methods: General
- Thema
-
Deconvolution
Donsker theorem
Efficiency
Distribution function
Smoothed empirical processes
Fourier multiplier
Schätztheorie
Theorie
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Söhl, Jakob
Trabs, Mathias
- Ereignis
-
Veröffentlichung
- (wer)
-
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
- (wo)
-
Berlin
- (wann)
-
2012
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Söhl, Jakob
- Trabs, Mathias
- Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
Entstanden
- 2012
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