Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal component
(TBATS) model.
Calls forecast::tbats() from package forecast.
Dictionary
This mlr3::Learner can be instantiated via the dictionary mlr3::mlr_learners or with the associated sugar function mlr3::lrn():
Meta Information
Task type: “fcst”
Predict Types: “response”, “quantiles”
Feature Types: “logical”, “integer”, “numeric”, “character”, “factor”, “ordered”, “POSIXct”, “Date”
Required Packages: mlr3, mlr3forecast, forecast
Parameters
| Id | Type | Default | Levels | Range |
| use.box.cox | logical | NULL | TRUE, FALSE | - |
| use.trend | logical | NULL | TRUE, FALSE | - |
| use.damped.trend | logical | NULL | TRUE, FALSE | - |
| seasonal.periods | untyped | NULL | - | |
| use.arma.errors | logical | NULL | TRUE, FALSE | - |
| use.parallel | untyped | - | - | |
| num.cores | integer | 2 | \([1, \infty)\) | |
| bc.lower | integer | 0 | \((-\infty, \infty)\) | |
| bc.upper | integer | 1 | \((-\infty, \infty)\) | |
| biasadj | logical | FALSE | TRUE, FALSE | - |
References
De Livera, A.M., Hyndman, R.J., Snyder &, D. R (2011). “Forecasting time series with complex seasonal patterns using exponential smoothing.” Journal of the American Statistical Association, 106(496), 1513–1527.
See also
Chapter in the mlr3book: https://mlr3book.mlr-org.com/chapters/chapter2/data_and_basic_modeling.html#sec-learners
Package mlr3learners for a solid collection of essential learners.
Package mlr3extralearners for more learners.
as.data.table(mlr_learners)for a table of available Learners in the running session (depending on the loaded packages).mlr3pipelines to combine learners with pre- and postprocessing steps.
Package mlr3viz for some generic visualizations.
Extension packages for additional task types:
mlr3proba for probabilistic supervised regression and survival analysis.
mlr3cluster for unsupervised clustering.
mlr3tuning for tuning of hyperparameters, mlr3tuningspaces for established default tuning spaces.
Other Learner:
LearnerFcst,
mlr_learners_fcst.adam,
mlr_learners_fcst.arfima,
mlr_learners_fcst.arima,
mlr_learners_fcst.auto_adam,
mlr_learners_fcst.auto_arima,
mlr_learners_fcst.auto_ces,
mlr_learners_fcst.bats,
mlr_learners_fcst.ces,
mlr_learners_fcst.ets,
mlr_learners_fcst.nnetar
Super classes
mlr3::Learner -> mlr3::LearnerRegr -> mlr3forecast::LearnerFcst -> mlr3forecast::LearnerFcstForecast -> LearnerFcstTbats