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Abstract: We present a new non-parametric estimator of the conditional density of thekernel type. It is based on an efficient transformation of the data by quantiletransform. By use of the copula representation, it turns out to have aremarkable product form. We study its asymptotic properties and compare itsbias and variance to competitors based on nonparametric regression.



Author: Olivier P. Faugeras LSTA

Source: https://arxiv.org/







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