Robust Mixture Regression Using Mixture of Different Distributions

  • Fatma Zehra Doğru
  • Olcay Arslan
Conference paper


In this paper, we examine the mixture regression model based on mixture of different type of distributions. In particular, we consider two-component mixture of normal-t distributions, and skew t-skew normal distributions. We obtain the maximum likelihood (ML) estimators for the parameters of interest using the expectation maximization (EM) algorithm. We give a simulation study and real data examples to illustrate the performance of the proposed estimators.


Mean Square Error Error Distribution Conditional Expectation Expectation Maximization Algorithm Stochastic Representation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors would like to thank referees and the editor for their constructive comments and suggestions that have considerably improved this work. The first author would like to thank the Higher Education Council of Turkey for providing financial support for Ph.D. study in Ankara University. The second author would like to thank the European Commission-JRC and the Indian Statistical Institute for providing financial support to attend the ICORS 2015 in Kolkata in India.


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Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.Faculty of Arts and Sciences, Department of StatisticsGiresun UniversityGiresunTurkey
  2. 2.Faculty of Science, Department of StatisticsAnkara UniversityAnkaraTurkey

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