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An implementation of several functions for feature extraction in ordinal time series datasets. Specifically, some of the features proposed by Weiss (2019) <doi:10.1080/01621459.2019.1604370> can be computed. These features can be used to perform inferential tasks or to feed machine learning algorithms for ordinal time series, among others. The package also includes some interesting datasets containing financial time series. Practitioners from a broad variety of fields could benefit from the general framework provided by 'otsfeatures'.
| Version: | 1.0.0 |
| Depends: | R (≥ 4.0.0) |
| Imports: | ggplot2, astsa, latex2exp, Rdpack, Bolstad2 |
| Published: | 2023-03-01 |
| DOI: | 10.32614/CRAN.package.otsfeatures |
| Author: | Angel Lopez-Oriona [aut, cre], Jose A. Vilar [aut] |
| Maintainer: | Angel Lopez-Oriona <oriona38 at hotmail.com> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| In views: | TimeSeries |
| CRAN checks: | otsfeatures results |
| Reference manual: | otsfeatures.pdf |
| Package source: | otsfeatures_1.0.0.tar.gz |
| Windows binaries: | r-devel: otsfeatures_1.0.0.zip, r-release: otsfeatures_1.0.0.zip, r-oldrel: otsfeatures_1.0.0.zip |
| macOS binaries: | r-release (arm64): otsfeatures_1.0.0.tgz, r-oldrel (arm64): otsfeatures_1.0.0.tgz, r-release (x86_64): otsfeatures_1.0.0.tgz, r-oldrel (x86_64): otsfeatures_1.0.0.tgz |
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