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Estimating the support of multivariate densities under measurement error

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  • Meister, Alexander
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    Abstract

    We consider the problem of estimating the support of a multivariate density based on contaminated data. We introduce an estimator, which achieves consistency under weak conditions on the target density and its support, respecting the assumption of a known error density. Especially, no smoothness or sharpness assumptions are needed for the target density. Furthermore, we derive an iterative and easily computable modification of our estimation and study its rates of convergence in a special case; a numerical simulation is given.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Multivariate Analysis.

    Volume (Year): 97 (2006)
    Issue (Month): 8 (September)
    Pages: 1702-1717

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    Handle: RePEc:eee:jmvana:v:97:y:2006:i:8:p:1702-1717

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    Related research

    Keywords: Deconvolution Errors-in-variables Multivariate density estimation Resampling Support estimation;

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