Clustering Effect on the Statistical Estimation Accuracy of Distribution Density |
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Authors: | Rimantas Rudzkis Tomas Ruzgas |
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Institution: | (1) Institute of Mathematics and Informatics, Akademijos 4, 08663 Vilnius, Lithuania |
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Abstract: | The paper is devoted to statistical nonparametric estimation of multivariate distribution density. The influence of data pre-clustering
on the estimation accuracy of multimodal density is analyzed by means of the Monte Carlo method. It is shown that the soft
clustering is more advantageous than the hard one. While a moderate increase in the number of clusters also increases the
calculation time, it considerably reduces the estimation error. |
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Keywords: | Multivariate distribution density Nonparametric estimation Data clustering |
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