A New Functional Clustering Method with Combined Dissimilarity Sources and Graphical Interpretation

Clustering is an essential task in functional data analysis. In this study, we propose a framework for a clustering procedure based on functional rankings or depth. Our methods naturally combine various types of between-cluster variation equally, which caters to various discriminative sources of fun...

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Detalles Bibliográficos

Autores principales:	Dai, Wenlin, Athanasiadis, Stavros, Mrkvička, Tomáš
Formato:	Capítulo de libro
Lenguaje:	inglés
Publicado:	IntechOpen 2021
Materias:	Physical Sciences, Engineering and Technology
Acceso en línea:	https://www.intechopen.com/chapters/79248
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