Nonparametric density estimation using a multidimensional mixture model of Gaussian distributions - Ruzgas, Tomas; Kavaliauskas, Mindaugas (Lietuvos matematikos rinkinys, 2005)
This paper algorithmically and empirically studies five major types of nonparametric multivariate density estimation techniques, where no assumption is made about data being drawn from any of known parametric families of distribution. There is developed method of inversion formula where noise cluster is included to general Gaussian mixture model.
Keywords: nonparametric density estimation; inversion formula; characteristic function