Abstract
Modeling based on finite mixture distributions is a rapidly developing area with an exploding range of applications. Finite mixture models are nowadays applied in such diverse areas as biology, biometrics, genetics, medicine, and marketing, among others. There are various features of finite mixture distributions that make them useful in statistical modeling. For instance, statistical models which are based on finite mixture distributions capture many specific properties of real data such as multimodality, skewness, kurtosis, and unobserved heterogeneity.
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Lachos Dávila, V.H., Cabral, C.R.B., Zeller, C.B. (2018). Motivation. In: Finite Mixture of Skewed Distributions. SpringerBriefs in Statistics(). Springer, Cham. https://doi.org/10.1007/978-3-319-98029-4_1
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DOI: https://doi.org/10.1007/978-3-319-98029-4_1
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