¹Giresun University, Faculty of Arts and Sciences, Department of Statistics, Giresun, Turkey. PhD. Email: fatma.dogru@giresun.edu.tr
²Ankara University, Faculty of Science, Department of Statistics, Ankara, Turkey. PhD. Email: oarslan@ankara.edu.tr

In this study, we explore a robust mixture regression procedure based on the skew t distribution in order to model heavy-tailed and/or skewed errors in a mixture regression setting. We present an EM-type algorithm to compute the maximum likelihood estimators for the parameters of interest using the scale mixture representation of the skew t distribution. The performance of proposed estimators is demonstrated by a simulation study and a real data example.

Key words: EM Algorithm, Maximum Likelihood, Mixture Regression Model, Skew t Distribution.

En este estudio se explora una mixtura robusta de modelos de regresión basada en la distribución t asimétrica, con el propósito de modelar colas pesadas o asimétricas en los errores, en un escenario de mixtura de regresiones. Se usa un algoritmo EM para obtener los estimadores máximo verosímiles empleando una mixtura de escala de la distribución t asimétrica. El comportamiento de los estimadores propuestos se ilustra a través de une estudio de simulación y de un ejemplo con datos reales.

Palabras clave: Algoritmo EM, máxima verosimilitud, mixtura de regresiones, distribución t asimétrica.

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