@misc{López-Lobato_Adriana_Laura_Fitting,
 author={López-Lobato, Adriana Laura and Avendano-Garrido, Martha L.},
 howpublished={online},
 publisher={Zielona Góra: Uniwersytet Zielonogórski},
 language={eng},
 abstract={A linear combination of Gaussian components is known as a Gaussian mixture model. It is widely used in data mining and pattern recognition. In this paper, we propose a method to estimate the parameters of the density function given by a Gaussian mixture model. Our proposal is based on the Gini index, a methodology to measure the inequality degree between two probability distributions, and consists in minimizing the Gini index between an empirical distribution for the data and a Gaussian mixture model. We will show several simulated examples and real data examples, observing some of the properties of the proposed method.},
 type={artykuł},
 title={Fitting a Gaussian mixture model through the Gini index},
 keywords={Gini index problem, Gaussian mixture model, clustering},
}