dissvar {TraMineR}R Documentation

Dissimilarity based pseudo variance

Description

Compute the pseudo variance based on the dissimilarity between object.

Usage

dissvar(diss)

Arguments

diss A dissimilarity matrix or a dist object (see dist)

Details

In the euclidian 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

This function generalized this concept by allowing to use any kind of dissimilarity to compute a pseudo variance term.

Value

Return the pseudo variance.

References

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.

See Also

dissassoc to test association between dissimilarity and another variable

disstree to analyse dissimilarities using induction trees

dissreg to analyse dissimilarities in a way close to linear regression

disscenter to compute the distance of each object to its center of group using dissimilarities

Examples

## 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))

[Package TraMineR version 1.1 Index]