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TraMineR
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TraMineR

Overview
Synopsis

TraMineR is a R-package for mining, describing and visualizing sequences of states or events, and more generally discrete sequence data.

Category

Data Mining Software Free

Features

Intended for mining, describing and visualizing sequences of states or events, and more generally discrete sequence data
Individual longitudinal characteristics of sequences
Sequence transversal characteristics by age point
Parallel coordinate plot of event sequences
Identifying most discriminating event subsequences

License

Open Source

Price

Free

Pricing

Subscription

Free Trial

Available

Users Size

Small (<50 employees), Medium (50 to 1000 employees), Enterprise (>1001 employees)

Website
Company

TraMineR

Rating
Our Rating
User Rating
Ease of use
7.6
Features & Functionality
7.6
Advanced Features
7.6
Integration
7.6
Customer Support
7.6
Performance
7.6
Training
Implementation
Renew & Recommend
Bottom Line

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.

7.6
Our Rating
User Rating
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TraMineR represents R-package (free software environment for statistical computing and graphics which compiles and runs on a wide variety of platforms such as UNIX platforms, Windows and MacOS) intended for mining, describing and visualizing sequences of states or events, and more generally discrete sequence data. Analysis of biographical longitudinal, data such as data describing careers or family trajectories, in the social sciences is its primary goal. This platform has many features that can apply in many other kinds of categorical sequence data. These features 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 such as 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. By using this platform users can load the library and the data set and retrieve the list of possible states. Next step is creating a state sequence object and by using this sequence object users can visualize the sequence data set, explore the sequence data set by computing and visualizing descriptive statistics, build a typology of transitions from school to work, run discrepancy analyses to study how sequences are related to covariates and to analyze event sequences.

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Ease of use
Features & Functionality
Advanced Features
Integration
Customer Support
Performance
Training
Implementation
Renew & Recommend

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