# seqsmooth

From seqhandbook v0.1.0
by Nicolas Robette

##### Smoothing sequence data

Smoothing of sequence data, using for each sequence the medoid of the sequences in its neighborhood. The results can be used to get a smoothed index plot.

- Keywords
- state sequences, Longitudinal characteristics

##### Usage

`seqsmooth(seqdata, diss, k=20, r=NULL)`

##### Arguments

- seqdata
a sequence object (see

`seqdef`

function).- diss
a dissimilarity matrix, giving the pairwise distances between sequences.

- k
size of the neighborhood. Default is 20.

- r
radius of the neighborhood. If NULL (default), the radius is not used for smoothing.

##### Value

A list with the following elements:

a sequence object (see `seqdef`

function)

pseudo-R2 measure of the goodness of fit of the smoothing

stress measure of the goodness of fit of the smoothing

##### References

Piccarreta R. (2012). Graphical and Smoothing Techniques for Sequence Analysis, *Sociological Methods and Research*, Vol. 41(2), 362-380.

##### Examples

```
# NOT RUN {
data(trajact)
seqact <- seqdef(trajact)
dissim <- seqdist(seqact, method="LCS")
mds <- cmdscale(dissim, k=1)
smoothed <- seqsmooth(seqact, dissim, k=30)$seqdata
seqIplot(smoothed, sortv=mds, xtlab=14:50, with.legend=FALSE, yaxis=FALSE, ylab=NA)
# }
```

*Documentation reproduced from package seqhandbook, version 0.1.0, License: GPL (>= 2)*

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