Package: MEDseq 1.4.1

MEDseq: Mixtures of Exponential-Distance Models with Covariates

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.

Authors:Keefe Murphy [aut, cre], Thomas Brendan Murphy [ctb], Raffaella Piccarreta [ctb], Isobel Claire Gormley [ctb]

MEDseq_1.4.1.tar.gz
MEDseq_1.4.1.zip(r-4.5)MEDseq_1.4.1.zip(r-4.4)MEDseq_1.4.1.zip(r-4.3)
MEDseq_1.4.1.tgz(r-4.4-any)MEDseq_1.4.1.tgz(r-4.3-any)
MEDseq_1.4.1.tar.gz(r-4.5-noble)MEDseq_1.4.1.tar.gz(r-4.4-noble)
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MEDseq.pdf |MEDseq.html✨
MEDseq/json (API)
NEWS

# Install 'MEDseq' in R:
install.packages('MEDseq', repos = c('https://keefe-murphy.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/keefe-murphy/medseq/issues

Datasets:
  • biofam - Family life states from the Swiss Household Panel biographical survey
  • mvad - MVAD: Transition from school to work

On CRAN:

distance-based-clusteringmixture-of-expertsmodel-based-clusteringsequence-analysis

4.72 score 5 stars 21 scripts 324 downloads 15 exports 35 dependencies

Last updated 12 months agofrom:3114fb0917. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 26 2024
R-4.5-winOKOct 26 2024
R-4.5-linuxOKOct 26 2024
R-4.4-winOKOct 26 2024
R-4.4-macOKOct 26 2024
R-4.3-winOKOct 26 2024
R-4.3-macOKOct 26 2024

Exports:dbsdist_freqwHget_MEDseq_resultsMEDseq_AvePPMEDseq_clustnamesMEDseq_compareMEDseq_controlMEDseq_entropyMEDseq_fitMEDseq_meantimeMEDseq_nameclustsMEDseq_newsMEDseq_stderrseqdefwKModes

Dependencies:bootcaclustercodetoolscolorspacedigestdoFuturefastclusterforeachfuturefuture.applygclusglobalsiteratorslatticelistenvMASSMatrixmatrixStatsmgcvnlmennetparallellypermuteprogressrqapRColorBrewerregistryseriationstringdistTraMineRTSPveganvegclustWeightedCluster

MEDseq: Mixtures of Exponential-Distance Models with Covariates

Keefe Murphy

Rendered fromMEDseq.Rmdusingknitr::rmarkdownon Oct 26 2024.

Last update: 2023-12-12
Started: 2019-08-23