Abstract
In this chapter we consider a flexible class of probability distributions, convenient for modeling data with skewness behavior, discrepant observations, and population heterogeneity. The elements of this family are convex linear combinations of densities that are scale mixtures of skew-normal distributions. An EM-type algorithm for maximum likelihood estimation is developed and the observed information matrix is obtained.
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Lachos Dávila, V.H., Cabral, C.R.B., Zeller, C.B. (2018). Univariate Mixture Modeling Using SMSN Distributions. In: Finite Mixture of Skewed Distributions. SpringerBriefs in Statistics(). Springer, Cham. https://doi.org/10.1007/978-3-319-98029-4_4
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DOI: https://doi.org/10.1007/978-3-319-98029-4_4
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