dissvar {TraMineR} | R Documentation |
Compute the discrepancy from the pairwise dissimilarities between objects. The discrepancy is a measure of dispersion of the set of objects.
dissvar(diss)
diss |
A dissimilarity matrix or a dist object (see dist ) |
The discrepancy is an extension of the concept of variance to other kind of objects for which we have a dissimilarity measure. The discrepancy
s^2
is defined as:
s^2=(1/2n^2)* sum sum d_ij
Mathematical ground: In the Euclidean case, the sum of square can be rewritten as:
SS= sum (y_i-y_mean)^2=(1/2n)*sum sum (y_i-y_j)^2
The concept of discrepancy generalize the equation by replacing the term
(y_i-y_j)^2
by another measure of dissimilarities.
The pseudo variance.
Studer, M., G. Ritschard, A. Gabadinho and N. S. Müller (2009). Analyse de dissimilarités par arbre d'induction. Revue des Nouvelles Technologies de l'Information, EGC'2009.
Batagelj, V. (1988). Generalized ward and related clustering problems. In H. Bock (Ed.), Classification and related methods of data analysis, pp. 67-74. North-Holland, Amsterdam.
Anderson, M. J. (2001). A new method for non-parametric multivariate analysis of variance. Austral Ecology 26, 32-46.
dissassoc
to test association of objects characterized by their dissimilarities with some explanatory variable
disstree
to analyse dissimilarities with induction trees
dissmfac
to analyse dissimilarities in a way close to linear regression
disscenter
to compute the distance of each object to its group center from a dissimilarity matrix
## Defining a state sequence object data(mvad) mvad.seq <- seqdef(mvad[, 17:86]) ## Building dissimilarities mvad.lcs <- seqdist(mvad.seq, method="LCS") ## Pseudo variance of the sequences print(dissvar(mvad.lcs))