An Iterative Procedure for Obtaining Maximum-Likelihood Estimates of the Parameters for a Mixture of Normal Distributions

This paper addresses the problem of obtaining numerically maximum-likelihood estimates of the parameters for a mixture of normal distributions. In recent literature, a certain successive-approximations procedure, based on the likelihood equations, was shown empirically to be effective in numerically...

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Veröffentlicht in:	SIAM journal on applied mathematics 1978-09, Vol.35 (2), p.362-378
Hauptverfasser:	Peters, B. Charles, Walker, Homer F.
Format:	Artikel
Sprache:	eng
Schlagworte:	Applied mathematics Approximation Consistent estimators Density estimation Estimates Gaussian distributions Infinity Inner products Mathematical independent variables Mathematical procedures Mathematical vectors Numerical analysis Perceptron convergence procedure Random variables Sample size
Online-Zugang:	Volltext
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