Comm. in Numerical Methods in Engineering, 13 (1997), pp. 755-763.
Ömer Egecioglu and Ashok Srinivasan
A Fast Non-Parametric Density Estimation Algorithm
Abstract.
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 $n^2$ 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.
omer@cs.ucsb.edu