Dissimilarités de type sphérique et positionnement multidimensionnel normé
Dissimilarites de type spherique et positionnement multidimensionnel normé
Our concern here, is the characterization of dissimilarity indexes defined over finite sets, whose spatial representation is spherical. Consequently, we propose a methodology (Normed MultiDimensional Scaling) to determine the spherical euclidean representation of a set of items best accounting for the initial dissimilarity between items. This methodology has the advantage of being graphically readable on individual qualities of projection like the normed PCA, of which it constitutes a generalization....
Distance à centre additive
Longitudinal K-sets analysis using a dummy time variable.
Longitudinal K-sets analysis using lagged variables.
We present an application of nonlinear Generalised Canonical Analysis (GCA) for analysing longitudinal data. The application uses lagged versions of variables to accomodate the time-dependence in the measurements. The usefulness of the proposed method is illustrated in an example from developmental psychology, in which we explore the relationship between mother and child dyadic interaction during the first six months after birth, demonstrating how child behaviour can elicit mother behaviour. We...
Mining and visualizing scientific publication data from Vojvodina.