disscenter {TraMineR} | R Documentation |
Compute the distance to a group center according to a matrix of distance. The method use the decomposition of distance used by the Ward criteria.
disscenter(diss, group=NULL, medoids.index=FALSE, max.iter=20)
diss |
A matrix of dissimilarity such as the one computed by seqdist , or a "dist" object |
group |
If null, only one group is considered, otherwise group to compute center |
medoids.index |
If TRUE, return the index of the first encontered most central sequence. One index per group is returned. |
max.iter |
Maximum number of iteration to trim the outliers |
A vector with the distance to center of group for each sequence, or a list of medoid index
dissvar
to compute pseudo variance using dissimilarities and for a basic introduction to concepts of pseudo variance analysis
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
## Defining a state sequence object data(mvad) mvad.seq <- seqdef(mvad[, 17:86]) ## Building dissimilarities mvad.lcs <- seqdist(mvad.seq, method="LCS") ## Compute distance to center according to group gcse5eq dc <- disscenter(mvad.lcs,group=mvad$gcse5eq) ## Ploting distribution of dissimilarity to center boxplot(dc~mvad$gcse5eq, col="cyan")