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 various normalisation methods (min-max, z-score, Box-Cox, Yeo-Johnson), and forecasting accuracy measures are implemented.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.1.0 |
rolling linux/jammy R-4.5 | TSrepr_1.1.0.tar.gz |
717.6 KiB |
1.1.0 |
rolling linux/noble R-4.5 | TSrepr_1.1.0.tar.gz |
721.1 KiB |
1.1.0 |
rolling source/ R- | TSrepr_1.1.0.tar.gz |
524.6 KiB |
1.1.0 |
latest linux/jammy R-4.5 | TSrepr_1.1.0.tar.gz |
717.6 KiB |
1.1.0 |
latest linux/noble R-4.5 | TSrepr_1.1.0.tar.gz |
721.1 KiB |
1.1.0 |
latest source/ R- | TSrepr_1.1.0.tar.gz |
524.6 KiB |
1.1.0 |
2026-04-26 source/ R- | TSrepr_1.1.0.tar.gz |
524.6 KiB |
1.1.0 |
2026-04-23 source/ R- | TSrepr_1.1.0.tar.gz |
524.6 KiB |
1.1.0 |
2026-04-09 windows/windows R-4.5 | TSrepr_1.1.0.zip |
1.0 MiB |
1.1.0 |
2025-04-20 source/ R- | TSrepr_1.1.0.tar.gz |
524.6 KiB |