Kernel Density Estimators for Gaussian Mixture Models

The problem of nonparametric estimation of probability density function is considered. The performance of kernel estimators based on various common kernels and a new kernel K (see (14)) with both fixed and adaptive smoothing bandwidth is compared in terms of the symmetric mean absolute percentage e...

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Bibliographic Details
Main Authors: Tomas Ruzgas, Indrė Drulytė
Format: Article
Language:English
Published: Lietuvos statistikų sąjunga, Lietuvos statistikos departamentas 2013-12-01
Series:Lithuanian Journal of Statistics
Subjects:
Online Access:https://www.journals.vu.lt/statisticsjournal/article/view/13919