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 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
In views: TimeSeries
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-prerel: TSrepr_1.0.0.zip, r-release: TSrepr_1.0.0.zip, r-oldrel: TSrepr_1.0.0.zip
OS X binaries: r-prerel: TSrepr_1.0.0.tgz, r-release: TSrepr_1.0.0.tgz


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