mlr3forecast
Extending 'mlr3' to Time Series Forecasting
Extends the 'mlr3' package and ecosystem to time series forecasting. Provides forecasting tasks, learners, resampling strategies, performance measures, and 'mlr3pipelines' operators for time-series feature engineering. Machine learning regression learners can be turned into forecasters through recursive and direct multi-step strategies.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | mlr3forecast_0.1.0.tar.gz |
2.9 MiB |
0.1.0 |
rolling linux/noble R-4.5 | mlr3forecast_0.1.0.tar.gz |
2.9 MiB |
0.1.0 |
rolling source/ R- | mlr3forecast_0.1.0.tar.gz |
1.0 MiB |
0.1.0 |
latest linux/jammy R-4.5 | mlr3forecast_0.1.0.tar.gz |
2.9 MiB |
0.1.0 |
latest linux/noble R-4.5 | mlr3forecast_0.1.0.tar.gz |
2.9 MiB |
0.1.0 |
latest source/ R- | mlr3forecast_0.1.0.tar.gz |
1.0 MiB |
0.1.0 |
2026-04-23 source/ R- | mlr3forecast_0.1.0.tar.gz |
0 B |
Dependencies (latest)
Depends
- mlr3 (>= 1.7.0)
Imports
Suggests
- distributional
- fabletools
- feasts
- forecast (>= 9.0.2)
- ggplot2 (>= 3.4.0)
- greybox
- mlr3tuning
- nnfor (>= 0.9.9)
- prophet (>= 1.1.7)
- Rcatch22
- Rlgt (>= 0.2.3)
- rpart
- smooth (>= 4.4.0)
- testthat (>= 3.2.0)
- tidyselect
- timeSeries
- tsbox
- tscount (>= 1.4.3)
- tsfeatures
- tsibble
- tsibbledata
- vctrs
- vdiffr (>= 1.0.0)
- withr (>= 3.0.0)
- xts
- zoo