Onlineforecast: An R Package for Adaptive and Recursive Forecasting

Systems that rely on forecasts to make decisions, e.g. control or energy trading systems, require frequent updates of the forecasts. Usually, the forecasts are updated whenever new observations become available, hence in an online setting. We present the R package onlineforecast that provides a generalized setup of data and models for online forecasting. It has functionality for time-adaptive fitting of dynamical and non-linear models. The setup is tailored to enable the effective use of forecasts as model inputs, e.g. numerical weather forecast. Users can create new models for their particular applications and run models in an operational setting. The package also allows users to easily replace parts of the setup, e.g. using new methods for estimation. The package comes with comprehensive vignettes and examples of online forecasting applications in energy systems, but can easily be applied for online forecasting in all fields.

Automated summary

Online forecasting is crucial for decision-making systems that rely on forecasts. These systems require frequent updates and the ability to adapt to changing data and models. The R package onlineforecast provides a flexible setup for creating and running custom models in an operational setting.