Title :
Approximation of distribution and density functions
Abstract :
Stochastic approximation algorithms are used to construct least squares error approximations to density and distribution functions. The approximation is linear in terms of the parameters to be estimated. The only information available to the algorithm is a sequence of independent samples from the distribution of density being approximated.
Keywords :
Approximation algorithms; Automatic control; Density functional theory; Distribution functions; Force control; Integral equations; Least squares approximation; Pattern recognition; Random variables; Stochastic processes;
Journal_Title :
Proceedings of the IEEE
DOI :
10.1109/PROC.1967.5454
