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 various normalisation methods (min-max, z-score, Box-Cox, Yeo-Johnson), and forecasting accuracy measures are implemented.


Reference manual

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install.packages("TSrepr")

1.1.0 by Peter Laurinec, 6 years 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  


GPL-3 | file LICENSE license


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

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

Linking to Rcpp


Suggested by modeltime.


See at CRAN