Abstract
A method is proposed for quickly choosing the blur coefficients of kernel functions in a non-parametric estimate of a multidimensional probability density of Rosenblatt–Parzen type. The technique is based on the analysis of the asymptotic properties of a multidimensional probability density estimate. The properties of the fast algorithm for choosing the blur coefficients of a kernel probability density estimate are investigated.
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