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TSrepr: Time Series Representations

Methods for representations (i.e. dimensionality reduction, preprocessing, feature extraction) of time series to help more accurate and effective time series data mining. Non-data adaptive, data adaptive, model-based and data dictated (clipped) representation methods are implemented. Also various normalisation methods (min-max, z-score, Box-Cox, Yeo-Johnson), and forecasting accuracy measures are implemented.

Version: 1.1.0
Depends: R (≥ 2.10)
Imports: Rcpp (≥ 0.12.12), MASS, quantreg, wavelets, mgcv, dtt
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, ggplot2, data.table, moments, testthat
Published: 2020-07-13
DOI: 10.32614/CRAN.package.TSrepr
Author: Peter Laurinec ORCID iD [aut, cre]
Maintainer: Peter Laurinec <tsreprpackage at gmail.com>
BugReports: https://github.com/PetoLau/TSrepr/issues
License: GPL-3 | file LICENSE
URL: https://petolau.github.io/package/, https://github.com/PetoLau/TSrepr/
NeedsCompilation: yes
Citation: TSrepr citation info
Materials: NEWS
In views: TimeSeries
CRAN checks: TSrepr results

Documentation:

Reference manual: TSrepr.pdf
Vignettes: Extending TSrepr
Time series representations in R
Use case: clustering time series representations

Downloads:

Package source: TSrepr_1.1.0.tar.gz
Windows binaries: r-devel: TSrepr_1.1.0.zip, r-release: TSrepr_1.1.0.zip, r-oldrel: TSrepr_1.1.0.zip
macOS binaries: r-release (arm64): TSrepr_1.1.0.tgz, r-oldrel (arm64): TSrepr_1.1.0.tgz, r-release (x86_64): TSrepr_1.1.0.tgz, r-oldrel (x86_64): TSrepr_1.1.0.tgz
Old sources: TSrepr archive

Reverse dependencies:

Reverse suggests: modeltime

Linking:

Please use the canonical form https://CRAN.R-project.org/package=TSrepr to link to this page.

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.