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'.">

otsfeatures: Ordinal Time Series Analysis (original) (raw)

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
License: GPL-2
NeedsCompilation: no
In views: TimeSeries
CRAN checks: otsfeatures results

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