Kernel density estimation (KDE) is a cornerstone of non-parametric statistics, offering a flexible means to infer an underlying probability density from finite samples without assuming a predetermined ...
In this paper we show how one canimplement in practice the bandwidth selection in deconvolution recursive kernel estimators of a probability density function defined by the stochastic approximation ...
Density-functional theory (DFT) is a rigorous and (in principle) exact framework for the description of the ground state properties of atoms, molecules and solids based on their electron density.
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