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A semiparametric density estimator based on elliptical distributions

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  • Liebscher, Eckhard

Abstract

In the paper we study a semiparametric density estimation method based on the model of an elliptical distribution. The method considered here shows a way to overcome problems arising from the curse of dimensionality. The optimal rate of the uniform strong convergence of the estimator under consideration coincides with the optimal rate for the usual one-dimensional kernel density estimator except in a neighbourhood of the mean. Therefore the optimal rate does not depend on the dimension. Moreover, asymptotic normality of the estimator is proved.

Suggested Citation

  • Liebscher, Eckhard, 2005. "A semiparametric density estimator based on elliptical distributions," Journal of Multivariate Analysis, Elsevier, vol. 92(1), pages 205-225, January.
    • Handle: RePEc:eee:jmvana:v:92:y:2005:i:1:p:205-225
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    References listed on IDEAS

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    1. Liebscher E., 1998. "On A Class Of Plug-In Methods Of Bandwidth Selection For Kernel Density Estimators," Statistics & Risk Modeling, De Gruyter, vol. 16(3), pages 229-244, March.
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    Cited by:

    1. Sigve Hovda, 2014. "Using pseudometrics in kernel density estimation," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(4), pages 669-696, December.
    2. Heather Battey & Oliver Linton, 2013. "Nonparametric estimation of multivariate elliptic densities via finite mixture sieves," CeMMAP working papers 15/13, Institute for Fiscal Studies.
    3. Sladana Babic & Laetitia Gelbgras & Marc Hallin & Christophe Ley, 2019. "Optimal tests for elliptical symmetry: specified and unspecified location," Working Papers ECARES 2019-26, ULB -- Universite Libre de Bruxelles.
    4. Rutger van der Spek & Alexis Derumigny, 2022. "Fast estimation of Kendall's Tau and conditional Kendall's Tau matrices under structural assumptions," Papers 2204.03285, arXiv.org.
    5. Battey, Heather & Linton, Oliver, 2014. "Nonparametric estimation of multivariate elliptic densities via finite mixture sieves," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 43-67.
    6. Eckhard Liebscher & Wolf-Dieter Richter, 2016. "Estimation of Star-Shaped Distributions," Risks, MDPI, vol. 4(4), pages 1-37, November.
    7. Liebscher, Eckhard & Okhrin, Ostap, 2023. "Semiparametric estimation of the high-dimensional elliptical distribution," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
    8. Derumigny, A. & Fermanian, J.-D., 2022. "Identifiability and estimation of meta-elliptical copula generators," Journal of Multivariate Analysis, Elsevier, vol. 190(C).
    9. Hallin, Marc & Paindaveine, Davy, 2009. "Optimal tests for homogeneity of covariance, scale, and shape," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 422-444, March.
    10. Liebscher Eckhard, 2023. "Constructing models for spherical and elliptical densities," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-19, January.
    11. Heather Battey & Oliver Linton, 2013. "Nonparametric estimation of multivariate elliptic densities via finite mixture sieves," CeMMAP working papers 41/13, Institute for Fiscal Studies.

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