TraMineRextras: seqedist – R documentation

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seqedist

Distances between event sequences

Description

Compute Optimal Matching like distances between event sequences. The distance measure is fully described in Studer et al. 2010.

Usage

seqedist(seqe, idcost, vparam, interval="No", norm="YujianBo")

Arguments

`seqe`	an event sequence object as defined by the `seqecreate` function.
`idcost`	Insertion/deletion cost of the different type of event (one entry per event type).
`vparam`	The cost of moving an event of one time unit.
`norm`	Character. One of `"YujianBo"` (respects triangle inequality), `"max"` (maximum distance) or `"none"`.
`interval`	Character. One of `"No"` (absolute ages), `"previous"` (time spent since previous event) or `"next"` (time spent until next event).

Value

a distance matrix.

Author(s)

Matthias Studer

References

Studer, M., Müller, N.S., Ritschard, G. & Gabadinho, A. (2010), "Classer, discriminer et visualiser des séquences d'événements", In Extraction et gestion des connaissances (EGC 2010), Revue des nouvelles technologies de l'information RNTI. Vol. E-19, pp. 37-48.

Ritschard, G., Bürgin, R., and Studer, M. (2014), "Exploratory Mining of Life Event Histories", In McArdle, J.J. & Ritschard, G. (eds) Contemporary Issues in Exploratory Data Mining in the Behavioral Sciences. Series: Quantitative Methodology, pp. 221-253. New York: Routledge.

Examples

data(actcal.tse)
actcal.seqe <- seqecreate(actcal.tse[1:200,])[1:6,]
## We have 8 different event in this dataset
idcost <- rep(1, 8)
dd <- seqedist(actcal.seqe, idcost=idcost, vparam=.1)

TraMineRextras

TraMineR Extension

v0.6.1

GPL (>= 2)

Authors

Gilbert Ritschard [aut, cre, ths, cph] (<https://orcid.org/0000-0001-7776-0903>), Matthias Studer [aut] (<https://orcid.org/0000-0002-6269-1412>), Reto Buergin [aut], Tim Liao [ctb], Alexis Gabadinho [ctb], Pierre-Alexandre Fonta [ctb], Nicolas Muller [ctb], Patrick Rousset [ctb]

Initial release

2021-01-20