# zbMATH — the first resource for mathematics

##### Examples
 Geometry Search for the term Geometry in any field. Queries are case-independent. Funct* Wildcard queries are specified by * (e.g. functions, functorial, etc.). Otherwise the search is exact. "Topological group" Phrases (multi-words) should be set in "straight quotation marks". au: Bourbaki & ti: Algebra Search for author and title. The and-operator & is default and can be omitted. Chebyshev | Tschebyscheff The or-operator | allows to search for Chebyshev or Tschebyscheff. "Quasi* map*" py: 1989 The resulting documents have publication year 1989. so: Eur* J* Mat* Soc* cc: 14 Search for publications in a particular source with a Mathematics Subject Classification code (cc) in 14. "Partial diff* eq*" ! elliptic The not-operator ! eliminates all results containing the word elliptic. dt: b & au: Hilbert The document type is set to books; alternatively: j for journal articles, a for book articles. py: 2000-2015 cc: (94A | 11T) Number ranges are accepted. Terms can be grouped within (parentheses). la: chinese Find documents in a given language. ISO 639-1 language codes can also be used.

##### Operators
 a & b logic and a | b logic or !ab logic not abc* right wildcard "ab c" phrase (ab c) parentheses
##### Fields
 any anywhere an internal document identifier au author, editor ai internal author identifier ti title la language so source ab review, abstract py publication year rv reviewer cc MSC code ut uncontrolled term dt document type (j: journal article; b: book; a: book article)
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 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.
##### MSC:
 62H30 Classification and discrimination; cluster analysis (statistics) 62-07 Data analysis (statistics)