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Multiplicative Bias Corrected Nonparametric Smoothers with Application to Nuclear Energy Spectrum Estimation
Hengartner N., Matzner-Lober E., Rouvière L., Burr T.
http://hal.archives-ouvertes.fr/hal-00408696
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Mathematics/Statistics
Statistics/Statistics Theory
Multiplicative Bias Corrected Nonparametric Smoothers with Application to Nuclear Energy Spectrum Estimation
Nicolas Hengartner 1, Eric Matzner-Lober () 2, Laurent Rouvière ( ) 2, 3, Thomas Burr 1
1:  Theorical Division (LANL)
Los Alamos National Laboratory,
Los Alamos, NM 87545
United States
2:  Institut de Recherche Mathématique de Rennes (IRMAR)
http://irmar.univ-rennes1.fr/
CNRS : UMR6625 – Université de Rennes 1 – École normale supérieure de Cachan - ENS Cachan – Institut National des Sciences Appliquées (INSA) : - RENNES – Université de Rennes II - Haute Bretagne
France
3:  Centre de Recherche en Économie et Statistique (CREST)
http://www.crest.fr/
INSEE – École Nationale de la Statistique et de l'Administration Économique
France
The paper presents a multiplicative bias reduction estimator for nonparametric regression. The approach consists to apply a multiplicative bias correction to an oversmooth pilot estimator. We study the asymptotic properties of the resulting estimate and prove that this estimate has zero asymptotic bias and the same asymptotic variance as the local linear estimate. Simulations show that our asymptotic results are available for small sample sizes. We also illustrate the benefit of this new method on nuclear energy spectrum estimation.
English
2009-07-30

Nonparametric regression – bias reduction – local linear estimate
20 pages

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TEX
paper_v10.tex(41.4 KB)
4fonc_tests.ps(81 KB)
biais_var_m2.ps(27.2 KB)
bias_variance.ps(24 KB)
energySpectrum.ps(30.4 KB)
num_ex.ps(44.1 KB)
biblio.bib(11.1 KB)
paper_v10.bbl(4.1 KB)
PDF
paper_v10.pdf(258 KB)
PS
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