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 min-max and z-score normalisations, and forecasting accuracy measures are implemented.
Version: | 1.0.0 |
Depends: | R (≥ 2.10) |
Imports: | Rcpp (≥ 0.12.12), MASS, quantreg, wavelets, mgcv, dtt |
LinkingTo: | Rcpp |
Suggests: | knitr, rmarkdown, ggplot2, data.table, moments |
Published: | 2018-01-26 |
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 |
CRAN checks: | TSrepr results |
Reference manual: | TSrepr.pdf |
Vignettes: |
Vignette Title Vignette Title Vignette Title |
Package source: | TSrepr_1.0.0.tar.gz |
Windows binaries: | r-devel: TSrepr_1.0.0.zip, r-release: TSrepr_1.0.0.zip, r-oldrel: TSrepr_1.0.0.zip |
OS X El Capitan binaries: | r-release: TSrepr_1.0.0.tgz |
OS X Mavericks binaries: | r-oldrel: not available |
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