The TBATS model is a time series model for series exhibiting multiple complex seasonalities.
The TBATS model was introduced by De Livera, Hyndman & Snyder (2011, JASA). "TBATS" is an acronym denoting its salient features:
- T for trigonometric regressors to model multiple-seasonalities
- B for Box-Cox transformations
- A for ARMA errors
- T for trend
- S for seasonality
The TBATS model is a generalization of the BATS model, which is similar except for lacking the trigonometric regressors.
The TBATS model can be fitted using the tbats() command in the forecast package for R.
