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.


News

TSrepr 1.0.2 2018/11/21

  • New accuracy measure MAAPE (mean arctangent absolute percentage error) was added
  • Added new references to vignettes
  • Added new references to documentation
  • Fixed some bad alignments in documentation

TSrepr 1.0.1 2018/05/31

  • Created unit tests (by testthat) for all functions
  • Fixed vignette titles
  • New citation of package (CITATION file in \inst)
  • ORCID in DESCRIPTION

TSrepr 1.0.0 2018/01/26

  • First CRAN release

Reference manual

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install.packages("TSrepr")

1.0.3 by Peter Laurinec, 2 months ago


https://petolau.github.io/package/, https://github.com/PetoLau/TSrepr/


Report a bug at https://github.com/PetoLau/TSrepr/issues


Browse source code at https://github.com/cran/TSrepr


Authors: Peter Laurinec [aut, cre]


Documentation:   PDF Manual  


Task views: Time Series Analysis


GPL-3 | file LICENSE license


Imports Rcpp, MASS, quantreg, wavelets, mgcv, dtt

Suggests knitr, rmarkdown, ggplot2, data.table, moments, testthat

Linking to Rcpp


See at CRAN