seqdiff {TraMineR}R Documentation

Decompose the difference between groups of sequences

Description

Decompose the difference between groups of sequences

Usage

seqdiff(seqdata, group, cmprange = c(0, 1), 
        seqdist_arg=list(method="LCS",norm=TRUE))

Arguments

seqdata The sequence to analyse
group The group variable
cmprange The range used to compare subsequences
seqdist_arg argument passed directly to seqdist as a list

Details

Analyses at each timestamp the sequence discrepancy within a sliding time window (of range defined by cmprange) that is explained by the group variable. The method computes a distance matrix, using seqdist at each timestamp and then derives the explained discrepancy with dissassoc.

There are print and plot methods for the result returned.

Value

A seqdiff object, with the following items:

stat A data.frame with three statistics (PseudoF, PseudoR2 and PseudoT) for each timestamp of the sequence, see dissassoc
variance A data.frame with, at each time stamp, the discrepancy within each group defined by the group variable and for the whole population.

References

Studer, M., G. Ritschard, A. Gabadinho, and N. S. Müller (2009) Discrepancy analysis of complex objects using dissimilarities. In H. Briand, F. Guillet, G. Ritschard, and D. A. Zighed (Eds.), Advances in Knowledge Discovery and Management, Studies in Computational Intelligence. Berlin: Springer.

Studer, M., G. Ritschard, A. Gabadinho and N. S. Müller (2009) Analyse de dissimilarités par arbre d'induction. In EGC 2009, Revue des Nouvelles Technologies de l'Information, Vol. E-15, pp. 7-18.

See Also

dissassoc to analyse the association with the whole sequence

Examples

## Defining a state sequence object
data(mvad)
mvad.seq <- seqdef(mvad[, 17:86])

## Building dissimilarities
mvad.diff <- seqdiff(mvad.seq, group=mvad$gcse5eq)
print(mvad.diff)
plot(mvad.diff)
plot(mvad.diff, stat="Variance")

[Package TraMineR version 1.4-1 Index]