A Fast Non-Parametric Density Estimation Algorithm
Ömer Eğeci̇oğlu, Ashok Srinivasan · Communications in Numerical Methods in Engineering · 1997
Non-parametric density estimation is the problem of approximating the values of a probability density function, given samples from the associated distribution. Non-parametric estimation finds applications in discriminant analysis, cluster analysis, and flow calculations based on Smoothed Particle Hydrodynamics. Usual estimators make use of kernel functions, and require on the order of n2 arithmetic operations to evaluate the density at n sample points. We describe a sequence of special weight functions which requires almost linear number of operations in n for the same computation. © 1997 John Wiley & Sons, Ltd.