Finite Mixture Modelling Using the Skew Normal Distribution

  title={Finite Mixture Modelling Using the Skew Normal Distribution},
  author={Tsung I. Lin and Jack C. Lee and Shin Yi Yen},
Normal mixture models provide the most popular framework for modelling heterogeneity in a population with continuous outcomes arising in a variety of subclasses. In the last two decades, the skew normal distribution has been shown beneficial in dealing with asymmetric data in various theoretic and applied problems. In this article, we address the problem of analyzing a mixture of skew normal distributions from the likelihood-based and Bayesian perspectives, respectively. Computational… CONTINUE READING


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Publications referenced by this paper.
Showing 1-10 of 34 references

A probabilistic representation of the “skew-normal” distribution

N. Henze
Scand. J. Statist. 13, 271-275. • 1986
View 2 Excerpts
Highly Influenced

A class of distributions which includes the normal ones

A. Azzalini
Scand. J. Statist. 12, 171-178. • 1985
View 5 Excerpts
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