期刊
COMPUTATIONAL STATISTICS
卷 15, 期 1, 页码 73-87出版社
PHYSICA-VERLAG GMBH & CO
DOI: 10.1007/s001800050038
关键词
principal components; interval data; symbolic objects
The present paper deals with the study of continuous interval data by means of suitable Principal Component Analyses (PCA). Statistical units described by interval data can be assumed as special cases of Symbolic Objects (SO) (Diday, 1987). In Symbolic Data Analysis (SDA), these data are represented as hypercubes. In the present paper, we propose some extensions of the PCA with the aim of representing, in a space of reduced dimensions, images of such hypercubes, pointing out differences and similarities according to their structural features.
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