Research of comparative analysis of nonparametric density estimation by applying Monte Carlo method
Articles
Indrė Drulytė
Kaunas University of Technology
Tomas Ruzgas
Kaunas University of Technology
Published 2013-12-20
https://doi.org/10.15388/LMR.B.2013.02
PDF (Lithuanian)

Keywords

non-parametric estimation
density evaluation
kernel function

How to Cite

Drulytė, I. and Ruzgas, T. (2013) “Research of comparative analysis of nonparametric density estimation by applying Monte Carlo method”, Lietuvos matematikos rinkinys, 54(B), pp. 6–11. doi:10.15388/LMR.B.2013.02.

Abstract

This paper presents nonparametric statistical estimation of distribution density. The Monte Carlo  method is used to show the effects of kernel function for multimodal kernel density estimation. Here it is shown that the novel kernel function is effective for asymmetrical heavy tails distributions.

PDF (Lithuanian)

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