TraMineR: a toolbox for exploring sequence data
TraMineR is a R
-package for mining, describing and visualizing
sequences of states or events, and more generally discrete sequence data. Its primary aim is the analysis of biographical longitudinal data in the social sciences, such as data describing careers or family trajectories. However, most of its features also apply to many other kinds of categorical sequence data. They include:
- Handling of longitudinal data and conversion between various sequence formats
- Plotting sequences (density plot, frequency plot, index plot and more)
- Individual longitudinal characteristics of sequences (length, time in each state, longitudinal entropy, turbulence, complexity and more)
- Sequence transversal characteristics by age point (transversal state distribution, transversal entropy, modal state)
- Other aggregated characteristics (transition rates, average duration in each state, sequence frequency)
- Dissimilarities between pairs of sequences (Optimal matching, longest common subsequence, Hamming, Dynamic Hamming, Multichannel and more)
- Medoid and heterogeneity measure of a set of sequences
- Discovering and plotting representative sequences
- ANOVA-like analysis of sequences and tree structured ANOVA from dissimilarities
- Parallel coordinate plot of event sequences
- Extracting frequent event subsequences
- Identifying most discriminating event subsequences
- Association rules between subsequences
Click here for a short preview
of what TraMineR can do for you!
What does TraMineR stand for?
It is a contraction of Life Trajectory Miner for R (and was inspired by the authors' taste for Gewürztraminer wine).
Who is developing TraMineR?
TraMineR is developed at
the Institute of Demography and Socioeconomics (IDESO)
University of Geneva
, Switzerland under the responsibility of the TraMineR Scientific Committee. The development started in the project Mining event histories
funded by the Swiss National Foundation for Scientific Research
under grants FN-116416 and FN-122230 and currently continues within the individual project IP 214 of the NCCR LIVES - overcoming vulnerability: life course perspectives
TraMineR benefited also from contributions of Reto Bürgin
. Pierre-Alexandre Fonta
is currently preparing a major upgrade of the package.
Other R packages from the TraMineR team
TraMineRextras, TraMineR ancillary functions
seqdist2, all dissimilarity measures addressed in Studer & Ritschard (2016).
PST, Alexis Gabadinho's package for Probabilistic Suffix Trees
WeightedCluster, Matthias Studer's clustering package
vcrpart, Reto Bürgin's package for Tree-based varying coefficients for ordinal mixed regression models and generalized linear regression models.
Rsocialdata, Emmanuel Rousseaux's suite of packages for handling, documenting and describing data sets of survey data.
MmgraphR, Pauline Adamopoulou's package for rendering transition probabilities from Markov and Hidden Markov models by means of parallel coordinate plots.