RT info:eu-repo/semantics/article
T1 Constrained parsimonious model-based clustering
A1 García Escudero, Luis Ángel
A1 Mayo Iscar, Agustín
A1 Riani, Marco
K1 Model-based clustering
K1 Mixture modeling
K1 Constraints
K1 12 Matemáticas
AB A new methodology for constrained parsimonious model-based clustering is introduced, where some tuning parameter allows to control the strength of these constraints. The methodology includes the 14 parsimonious models that are often applied in model-based clustering when assuming normal components as limit cases. This is done in a natural way by filling the gap among models and providing a smooth transition among them. The methodology provides mathematically well-defined problems and is also useful to prevent us from obtaining spurious solutions. Novel information criteria are proposed to help the user in choosing parameters. The interest of the proposed methodology is illustrated through simulation studies and a real-data application on COVID data.
PB Springer
SN 0960-3174
YR 2021
FD 2021
LK https://uvadoc.uva.es/handle/10324/50994
UL https://uvadoc.uva.es/handle/10324/50994
LA eng
NO Statistics and Computing, 2021, vol. 32, n. 1.
NO Producción Científica
DS UVaDOC
RD 06-ago-2024