The existing robust methods for model-based classification and clustering deal with elliptically contoured components. Here we introduce robust estimation for mixtures of skew-normal, by the joint usage of trimming and constraints. The model allows to fit heterogeneous skew data with great flexibility.

Garcìa-Escudero, L., Greselin, F., Mayo-Iscar, A. (2015). Robust clustering for heterogeneous skew data. In F. Mola, C. Conversano (a cura di), CLADAG 2015 Book of Abstracts (pp. 154-157). Cagliari : CUEC.

Robust clustering for heterogeneous skew data

Greselin, F;
2015

Abstract

The existing robust methods for model-based classification and clustering deal with elliptically contoured components. Here we introduce robust estimation for mixtures of skew-normal, by the joint usage of trimming and constraints. The model allows to fit heterogeneous skew data with great flexibility.
Capitolo o saggio
Clustering, robust estimation, skew data
English
CLADAG 2015 Book of Abstracts
Mola, F; Conversano, C
ott-2015
2015
978-88-8467-949-9
CUEC
154
157
Garcìa-Escudero, L., Greselin, F., Mayo-Iscar, A. (2015). Robust clustering for heterogeneous skew data. In F. Mola, C. Conversano (a cura di), CLADAG 2015 Book of Abstracts (pp. 154-157). Cagliari : CUEC.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/176553
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