Discrepancy Analysis of State Sequences
By Matthias Studer, Gilbert Ritschard, Alexis Gabadinho, Nicolas S. Müller. 2011
223 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Networks and Communications, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/59ce4378d74656bc09d0ed0b159b8992cbc04fa4
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In Artificial Intelligence
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Citations in the corpus
- WeightedCluster Library Manual A practical guide to creating typologies of trajectories in the social sciences with R (2013, methodology): “Studer et al. (2011) gives an introduction to its implementation in R as well as a general presentation of the method.”
- Analyzing and Visualizing State Sequences in R with TraMineR (2011, unknown): “…also tools for event sequences such as finding the most frequent and most discriminating subse-quences and extracting association rules between subsequences, as well as tools for ANOVA-like analyses of sequences (Studer, Ritschard, Gabadinho, and M¨uller 2011) that will not be discussed here.”
- The stringdist Package for Approximate String Matching (2014, unknown): “The TraMineR package (Studer et al., 2011) for example implements various distance measures on 1The vwr package (Keuleers, 2013) used to offer its own implementation of string distances but currently depends on stringdist.”
- What matters in differences between life trajectories: a comparative review of sequence dissimilarity measures (2016, methodology): “For instance, Abbott (1983) mentioned multi-dimensional scaling, Massoni et al. (2009) used self-organizing maps, Studer et al. (2011) showed how to run analysis-of-variance like Address for correspondence: Matthias Studer, Institute for Demographic and Life Course Studies, University of Geneva,…”