Compute 'wcKMedoids' clustering for different number of...

This function automatically name the cluster using the sequence medoid of each cluster.

1 | ```
seqclustname(seqdata, group, diss, weighted = TRUE, perc = FALSE)
``` |

`seqdata` |
State sequence object (see |

`group` |
A vector of clustering membership. |

`diss` |
a dissimilarity matrix or a |

`weighted` |
Logical. If |

`perc` |
Logical. If |

A factor of clustering membership. The labels are defined using sequences medoids and optionnaly percentage of case in each cluster.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
data(mvad)
## Aggregating state sequence
aggMvad <- wcAggregateCases(mvad[, 17:86], weights=mvad$weight)
## Creating state sequence object
mvad.seq <- seqdef(mvad[aggMvad$aggIndex, 17:86], weights=aggMvad$aggWeights)
## Computing Hamming distance between sequence
diss <- seqdist(mvad.seq, method="HAM")
## KMedoids using PAMonce method (clustering only)
clust5 <- wcKMedoids(diss, k=5, weights=aggMvad$aggWeights)
clust5.labels <- seqclustname(mvad.seq, clust5$clustering, diss=diss, perc=TRUE)
seqdplot(mvad.seq, group=clust5.labels)
``` |

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