Geodesic
Robust estimation and its application to a classification problem
Mathematica Applicanda, Tome 47 (2019) no. 2, pp. 231-243.

Voir la notice de l'article provenant de la source Annales Societatis Mathematicae Polonae Series

In the article, a classification problem with two distributed classes is considered. The problem is solving using empirical discriminant functions for Gaussian classifier and estimators for unknown parameters of multivariate normal distribution. The three etimators, maximum likelihood estimator, Kulawik-Zontek estimator and minimum covariance determinant estimator, are compared in two different empirical examples (small size sample and large size sample).
DOI : 10.14708/ma.v47i2.6499
Classification : 62Jxx
Mots-clés : Gaussian classifier, Huber’s function, estimator, multivariate normal model 
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Henryk Gacki; Agnieszka Kulawik. Robust estimation and its application to a classification problem. Mathematica Applicanda, Tome 47 (2019) no. 2, pp.  231-243. doi : 10.14708/ma.v47i2.6499. http://geodesic.mathdoc.fr/articles/10.14708/ma.v47i2.6499/

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