TraMineR (version 1.1)

dissvar: 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)

Value

• Return the pseudo variance.

encoding

latin1

Details

In the euclidian case, the sum of square can be rewritten as: $$SS=\sum_{i=1}^{n}(y_i-\bar{y})^2=\frac{1}{2n}\sum_{i=1}^{n}\sum_{j=1}^{n}(y_i-y_j)^2$$ This function generalized this concept by allowing to use any kind of dissimilarity to compute a pseudo variance term.

References

Studer, M., G. Ritschard, A. Gabadinho and N. S. M�ller (2009). Analyse de dissimilarit�s 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))