[ABE-L] Seminário Conjunto UFSCar/ICMC - 19/06/2014 - 14h00 - DEs-UFSCar

[Carlos Diniz]

Seminário Conjunto UFSCar/ICMC – 19/06/2014 - 14h00

LOCAL: Sala de seminários – DEs-UFSCar 

TÍTULO: Regression Modeling based on Scale Mixtures of Skew-Normal Distributions

PALESTRANTE: Celso Cabral (UFAM)

 

RESUMO: 

The traditional estimation of mixture regression models is based on the assumption of normality (symmetry) of component errors and thus is sensitive to outliers, heavy-tailed errors and/or asymmetric errors. We present a proposal to deal with these issues simultaneously in the context of the mixture regression by 
extending the classical normal model by assuming that the random errors follow a scale mixtures of skew-normal distributions. This approach allows us to model data with great flexibility, accommodating skewness and heavy tails. The main virtue of considering the mixtures regression models under the class of 
scale mixtures of skew-normal distributions is that they have a nice hierarchical representation which allows an easy implementation of inference. We develop a simple EM-type algorithm to perform maximum likelihood inference of the parameters in the proposed model. In order to examine the robust aspect 
of this flexible model against outlying observations, some simulation studies have also been presented. Finally, a real data set has been analyzed, illustrating the usefulness of the proposed methodology. 

(Joint work with Camila B. Zeller - Federal University of Juiz de Fora and Víctor H. Lachos - Campinas State University)
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