Package: ctsfeatures 1.2.2

ctsfeatures: Analyzing Categorical Time Series

An implementation of several functions for feature extraction in categorical time series datasets. Specifically, some features related to marginal distributions and serial dependence patterns can be computed. These features can be used to feed clustering and classification algorithms for categorical time series, among others. The package also includes some interesting datasets containing biological sequences. Practitioners from a broad variety of fields could benefit from the general framework provided by 'ctsfeatures'.

Authors:Angel Lopez-Oriona [aut, cre], Jose A. Vilar [aut]

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ctsfeatures.pdf |ctsfeatures.html✨
ctsfeatures/json (API)

# Install 'ctsfeatures' in R:
install.packages('ctsfeatures', repos = c('https://anloor7.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 1 stars 1 scripts 232 downloads 16 exports 46 dependencies

Last updated 1 years agofrom:e611d41570. Checks:1 OK, 8 NOTE. Indexed: yes.

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Doc / VignettesOKMar 25 2025
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R-4.5-linuxNOTEMar 25 2025
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Exports:binarizationcalculate_featurescalculate_motifscalculate_subfeaturesconditional_probabilitiesjoint_probabilitiesmarginal_probabilitiesplot_cccplot_cohenplot_cramerplot_ctsplot_ifsctplot_mccplot_phplot_regplot_se

Dependencies:anytimeastsaBHBolstad2clicolorspacecpp11dplyrellipsisfansifarvergenericsggplot2gluegtableisobandlabelinglatex2explatticelifecyclelubridatemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6rbibutilsRColorBrewerRcppRdpackrlangscalesstringistringrtibbletidyselecttimechangetsibbleutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Constructs the binarized time series associated with a given categorical time seriesbinarization
Computes several features associated with a categorical time seriescalculate_features
Computes the relative frequency of motifs in a categorical time seriescalculate_motifs
Computes several subfeatures associated with a categorical time seriescalculate_subfeatures
Computes the conditional probabilities of a categorical time seriesconditional_probabilities
GeneticSequencesGeneticSequences
Computes the joint probabilities of a categorical time seriesjoint_probabilities
Computes the marginal probabilities of a categorical time seriesmarginal_probabilities
Constructs a control chart for the cycle lengths of a categorical seriesplot_ccc
Constructs a serial dependence plot based on Cohen's kappaplot_cohen
Constructs a serial dependence plot based on Cramer's viplot_cramer
Constructs a categorical time series plotplot_cts
Constructs the IFS circle transformation of a categorical time seriesplot_ifsct
Constructs a control chart for the marginal distribution of a categorical seriesplot_mcc
Constructs the pattern histogram associated with a given category of a categorical time seriesplot_ph
Constructs the rate evolution graph for a categorical time seriesplot_reg
Represents the spectral envelope of a categorical time seriesplot_se
ProteinSequencesProteinSequences
SleepStagesSleepStages
SyntheticData1SyntheticData1
SyntheticData2SyntheticData2
SyntheticData3SyntheticData3