Parsimony and parameter estimation for mixtures of multivariate leptokurtic-normal distributions

Mixtures of multivariate leptokurtic-normal distributions have been recently introduced in the clustering literature based on mixtures of elliptical heavy-tailed distributions. They have the advantage of having parameters directly related to the moments of practical interest. We derive two estimatio...

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Vydané v:	Advances in data analysis and classification Ročník 18; číslo 3; s. 597 - 625
Hlavní autori:	Browne, Ryan P., Bagnato, Luca, Punzo, Antonio
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2024 Springer Nature B.V
Predmet:	Algorithms Chemistry and Earth Sciences Clustering Computer Science Data Mining and Knowledge Discovery Economics Finance Fixed points (mathematics) Health Sciences Humanities Insurance Kurtosis Law Management Mathematics and Statistics Medicine Mixtures Multivariate analysis Parameter estimation Physics Regular Regular Article Simulation Statistical Theory and Methods Statistics Statistics for Business Statistics for Engineering Statistics for Life Sciences Statistics for Social Sciences Leptokurtic-normal distribution Mixture models Parsimony Majorization–minimization algorithm 62Hxx Multivariate analysis 62H12 Estimation in multivariate analysis 62G07 Density estimation 62H30 Classification and discrimination; cluster analysis (statistical aspects); mixture models
ISSN:	1862-5347, 1862-5355
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