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 sequential data. Its primary aim is the analysis of biographical longitudinal data in the social sciences, such as data describing careers or family trajectories. Most of its features also apply, however, to non temporal data such as text or DNA sequences for instance. 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)
- Centro-type and heterogeneity measure of a set of sequences
- Discovering and plotting representative sequences
- ANOVA-like analysis of sequences and tree structured ANOVA from dissimilarities
- 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 also inspired by the authors' taste for Gewürztraminer wine).
Who is developing TraMineR?
TraMineR is developed at
the
Institute for Demographic and Life Course Studies (IDEMO),
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 14 of the
NCCR LIVES - overcoming vulnerability: life course perspectives.
Scientific Committee
Reto Bürgin and
Emmanuel Rousseaux joined the development team in 2011.
Other R packages from the TraMineR team
-
TraMineRextras, TraMineR ancillary functions
-
PST, Alexis Gabadinho's package for Probabilistic Suffix Trees
-
WeightedCluster, Matthias Studer's clustering package
-
Dataset, Emmanuel Rousseaux's package for handling, documenting and describing data sets of survey data.
