Implements a model-based clustering method for categorical life-course sequences relying on mixtures of exponential-distance models introduced by Murphy et al. (2021) <doi:10.1111/rssa.12712>. A range of flexible precision parameter settings corresponding to weighted generalisations of the Hamming distance metric are considered, along with the potential inclusion of a noise component. Gating covariates can be supplied in order to relate sequences to baseline characteristics and sampling weights are also accommodated. The models are fitted using the EM algorithm and tools for visualising the results are also provided.
Version: 1.4.2 Depends: R (≥ 4.0.0) Imports: cluster, matrixStats (≥ 1.0.0), nnet (≥ 7.3-0), seriation, stringdist, TraMineR (≥ 2.2-10), WeightedCluster Suggests: knitr, rmarkdown, viridisLite (≥ 0.4.0) Published: 2025-03-10 DOI: 10.32614/CRAN.package.MEDseq Author: Keefe Murphy [aut, cre], Thomas Brendan Murphy [ctb], Raffaella Piccarreta [ctb], Isobel Claire Gormley [ctb] Maintainer: Keefe Murphy <keefe.murphy at mu.ie> BugReports: https://github.com/Keefe-Murphy/MEDseq/issues License: GPL (≥ 3) URL: https://cran.r-project.org/package=MEDseq NeedsCompilation: no Language: en-GB Citation: MEDseq citation info Materials: README NEWS CRAN checks: MEDseq results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=MEDseq to link to this page.
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