Nonparametric density estimation using a multidimensional mixture model of Gaussian distributions

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 clust...

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Bibliographic Details
Main Authors: Tomas Ruzgas, Mindaugas Kavaliauskas
Format: Article
Language:English
Published: Vilnius University Press 2005-12-01
Series:Lietuvos Matematikos Rinkinys
Subjects:
Online Access:https://www.journals.vu.lt/LMR/article/view/30856