Purpose of this work is to investigate on the use of the Integrated Squared Error, or L_2 distance, as a practical tool for parameters estimation of mixtures of two normal bivariates in presence of outliers, situations in which maximum likelihood estimators are usually unstable. Theory is outlined, closed expressions for the L_2 minimizing estimate criterion for bivariate gaussian mixtures are given. In order to evaluate robustness of maximum likelihood and $L_2$ minimizing estimate criteria we compare results arising from Montecarlo simulation for some mixtures of gaussian bivariates in occurrence of different outliers positioning and consistency, matching some typical situations that frequently arise in industrial and chemical fields.
On Robustness to Outliers of Parametric L2 Estimate Criterion in the case of Bivariate Normal Mixtures: a Simulation Study
DURIO, Alessandra;ISAIA, Ennio Davide
2004-01-01
Abstract
Purpose of this work is to investigate on the use of the Integrated Squared Error, or L_2 distance, as a practical tool for parameters estimation of mixtures of two normal bivariates in presence of outliers, situations in which maximum likelihood estimators are usually unstable. Theory is outlined, closed expressions for the L_2 minimizing estimate criterion for bivariate gaussian mixtures are given. In order to evaluate robustness of maximum likelihood and $L_2$ minimizing estimate criteria we compare results arising from Montecarlo simulation for some mixtures of gaussian bivariates in occurrence of different outliers positioning and consistency, matching some typical situations that frequently arise in industrial and chemical fields.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.