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     Research Journal of Applied Sciences, Engineering and Technology


Testing Homogeneity of Mixture of Skew-normal Distributions Via Markov Chain Monte Carlo Simulation

1Rahman Farnoosh 2Morteza Ebrahimi and 2SetarehDalirian
1Department of Mathematics, South Tehran Branch, Islamic Azad University, Tehran
2Department of Mathematics, Karaj Branch, Islamic Azad University, Karaj
3School of Mathematics, Iran University of Science and Technology, Narmak, Tehran 16846, Iran
Research Journal of Applied Sciences, Engineering and Technology  2015  2:112-117
http://dx.doi.org/10.19026/rjaset.10.2562  |  © The Author(s) 2015
Received: May 06, 2012  |  Accepted: July 09, 2012  |  Published: May 20, 2015

Abstract

The main purpose of this study is to intoduce an optimal penalty function for testing homogeneity of finite mixture of skew-normal distribution based on Markov Chain Monte Carlo (MCMC) simulation. In the present study the penalty function is considered as a parametric function in term of parameter of mixture models and a Baysian approach is employed to estimating the parameters of model. In order to examine the efficiency of the present study in comparison with the previous approaches, some simulation studies are presented.

Keywords:

Homogeneity test, markov chain monte carlo simulation, penalty function, skew-normal mixtures,


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Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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