Open AccessProbability density estimation using data projection
Author(s) -
Mindaugas Kavaliauskas
Publication year - 2009
Publication title -
lietuvos matematikos rinkinys
Language(s) - English
Resource type - Journals
eISSN - 2335-898X
pISSN - 0132-2818
DOI - 10.15388/lmr.2009.53
Subject(s) - multivariate kernel density estimation , kernel density estimation , estimator , density estimation , statistic , projection pursuit , nonparametric statistics , multivariate statistics , projection (relational algebra) , mathematics , probability density function , kernel (algebra) , statistics , computer science , variable kernel density estimation , algorithm , artificial intelligence , kernel method , combinatorics , support vector machine
Nonparametric estimation of multivariate multimodal probability density is analysed. The projection pursuit density estimator was proposed by J.H. Friedman. Author of this paper proposes the modifications of original Friedman algorithm: employing a kernel density estimator, and a projection index based on Kolmogorov–Smirnov statistic. The efficiency of proposed modifications is analysed using computer simulation technique.