A.S.I. 5 - 5th International Meeting Statistical Implicative Analisys

The 5th International Conference, to give continuation to previous meetings:

France: IUFM of Caen in 2000 (A.S.I 1)
Brazil: University PUC São Paulo in 2003 (A.S.I 2)
Italy: University of Palermo in 2005 (A.S.I 3)
Spain: University de Castellon in 2007 (A.S.I 4)

should provide the opportunity to welcome all who wish to contribute to the development of this approach, giving them the opportunity to communicate their work to bear on theoretical issues or applications

Origin and development of S.I.A.

Let us recall that this method of non-symmetrical data analysis allows us to extract and structure knowledge in the form of rules and general rules using a set of data that connects a population of subjects (or objects) with a set of variables. This method stems from the statistical modelling of the quasi-implication: if a given variable or conjunction of variables "a" is noticed among the population, then, in general, so will be variable "b". The variables referred to can be of various types: binary, modal, numerical, interval, etc. Contrary to the methods of symmetrical analysis based, for instance, on distance or correlation, groups of acquired rules can lead to hypotheses of causality. These groups are structured according to different supplementary approaches (implicative graph, oriented hierarchy). The quantitative determination of subjects or descriptors responsible for these structures is determined by their contribution or their typicality. Finally, the results and their interpretation can be readily visualized by means of the CHIC software (Classification Hiérarchique Implicative and Cohésitive).

Gras R., Suzuki E., Guillet F. and Spagnolo F. (Eds) (2008) Statistical Implicative Analysis, Springer-Verlag, Berlin-Heidelberg Consultable : http://www.springer.com/engineering/book/978-3-540-78982-6