Robust Mixture Regression Based on the Skew t Distribution

• FATMA ZEHRA Doğru ^[1] ; OLCAY ARSLAN ^[2]
  1. [1] Giresun University

     Giresun University

     Turquía

     
  2. [2] Ankara University

     Ankara University

     Turquía

     
• Localización: Revista Colombiana de Estadística, ISSN-e 2389-8976, ISSN 0120-1751, Vol. 40, Nº. 1, 2017, págs. 45-64
• Idioma: inglés
• DOI: 10.15446/rce.v40n1.53580
• Títulos paralelos:
  • Mixtura robusta de modelos de regresión basada en la distribución t asimétrica
• Enlaces
  • Texto completo
• Resumen
  • español

    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.

  • English

    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.

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