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Journal article
A fast non-parametric density estimation algorithm
Communications in Numerical Methods in Engineering, Vol.13, pp.755-763
13
1997
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 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.
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Details
- Title
- A fast non-parametric density estimation algorithm
- Publication Details
- Communications in Numerical Methods in Engineering, Vol.13, pp.755-763
- Resource Type
- Journal article
- Publisher
- John Wiley & Sons, Ltd.; United Kingdom
- Series
- 13
- Copyright
- 1997 John Wiley & Sons, Ltd.
- Identifiers
- 99380090781906600
- Academic Unit
- Computer Science; Hal Marcus College of Science and Engineering
- Language
- English