Resumen

SHIMIZU, Taciana; LOUZADA, Francisco  y  SUZUKI, Adriano. Finite Mixture of Compositional Regression With Gaussian Errors. Rev.Colomb.Estad. [online]. 2018, vol.41, n.1, pp.75-86. ISSN 0120-1751.  https://doi.org/10.15446/rce.v41n1.63152.

In this paper, we consider to evaluate the efficiency of volleyball players according to your performance of attack, block and serve, considering the compositional structure of the data related to the fundaments of this sport. In this way, we consider a nite mixture of regression model to compositional data. The maximum likelihood estimation of this model was obtained via an EM algorithm. A simulation study reveals that the parameters are correctly recovery. In addition, the estimators are asymptotically unbiased. By considering real dataset of Brazilian volleyball competition, we show that the model proposed presents best fit than the usual regression model.

Palabras clave : Compositional Data; Finite Mixture Regression; EM Algorithm.

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