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Non-symmetrical data analysis by statistical implication. (Analyse non symétrique de données par l’implication statistique.) (French) Zbl 0866.62034
Summary: Many methods of data analysis built data organisations according to a criterion of resemblance measured by different indices. Mostly, these indices are symmetrical. However, in multiple real situations, we need to structure a set of variables or a set of variable classes according to inclusion or inference relations such that: “If $a$ then $b$”. Our approach, inspired by the work of {\it I. C. Lerman}, [Classification et analyse ordinale des données. (1981; Zbl 0485.62051)], give us a direction to get an oriented classification of these variables, figured on a graph. Thus we obtain an oriented classification on different classes of variables represented by a hierarchy. In a next step, we examine the significant nodes of the latter as well as the contribution of subjects-objects considered individually or through a categorisation.
62H30Classification and discrimination; cluster analysis (statistics)
62-07Data analysis (statistics)
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