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