Title :
On estimation of a mixture of normal density functions
Author :
Young, T.Y. ; Coraluppi, G.
Author_Institution :
Carnegie-Mellon University, Pittsburgh, Pennsylvania
Abstract :
A stochastic approximation algorithm is developed for estimating a mixture of normal density functions with unknown means and unknown variances. The algorithm minimizes an information criterion which has interesting properties for density approximations. The question of the completeness of normal density functions for the approximation of the class of continuous probability density functions is analyzed.
Keywords :
Algorithm design and analysis; Approximation algorithms; Convergence; Density functional theory; Density measurement; Distribution functions; Equations; H infinity control; Probability density function; Stochastic processes;
Conference_Titel :
Adaptive Processes (8th) Decision and Control, 1969 IEEE Symposium on
Conference_Location :
University Park, PA, USA
DOI :
10.1109/SAP.1969.269929
