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Local Multiplicative Bias Correction for Asymmetric Kernel Density Estimator

Hagmann, Matthias
Year 2003
Collection Cahiers de recherche; 2003.20
Abstract We consider semiparametric asymmetric kernel density estimators when the unknown density has support on [ 0, infinity) We provide a unifying framework which contains asymmetric kernel versions of several semiparametric density estimators considered previously in the literature This framework allows us to use popular parametric models in a nonparametric fashion and yields estimators which are robust to misspecification We further develop a specification test to determine if a density belongs to a particular parametric family The proposed estimators outperform rival non- and semiparametric estimators in finite samples and are simple to implement We provide applications to loss data from a large Swiss health insurer and Brazilian income data.
Keywords Semiparametric density estimationAsymmetric kernelIncome distributionLoss distributionHealth insuranceSpecification testing
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HAGMANN, Matthias, SCAILLET, Olivier. Local Multiplicative Bias Correction for Asymmetric Kernel Density Estimator. 2003 https://archive-ouverte.unige.ch/unige:5788

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Deposited on : 2010-04-15

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