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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'.

Version: 1.2.2
Depends: R (≥ 4.0.0)
Imports: ggplot2, astsa, latex2exp, Rdpack, Bolstad2, tsibble
Suggests: testthat (≥ 3.0.0)
Published: 2024-01-29
Author: Angel Lopez-Oriona [aut, cre], Jose A. Vilar [aut]
Maintainer: Angel Lopez-Oriona <oriona38 at hotmail.com>
License: GPL-2
NeedsCompilation: no
CRAN checks: ctsfeatures results

Documentation:

Reference manual: ctsfeatures.pdf

Downloads:

Package source: ctsfeatures_1.2.2.tar.gz
Windows binaries: r-devel: ctsfeatures_1.2.2.zip, r-release: ctsfeatures_1.2.2.zip, r-oldrel: ctsfeatures_1.2.2.zip
macOS binaries: r-release (arm64): ctsfeatures_1.2.2.tgz, r-oldrel (arm64): ctsfeatures_1.2.2.tgz, r-release (x86_64): ctsfeatures_1.2.2.tgz, r-oldrel (x86_64): ctsfeatures_1.2.2.tgz
Old sources: ctsfeatures archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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