TSrepr: Time Series Representations (original) (raw)
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 |
| BugReports: | https://github.com/PetoLau/TSrepr/issues |
| License: | GPL-3 | file |
| 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 |
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