  This paper introduces an R package ForecastTB that can be used to compare the
accuracy of different forecasting methods as related to the characteristics of
a time series dataset. The ForecastTB is a plug-and-play structured module, and
several forecasting methods can be included with simple instructions. The
proposed test-bench is not limited to the default forecasting and error metric
functions, and users are able to append, remove, or choose the desired methods
as per requirements. Besides, several plotting functions and statistical
performance metrics are provided to visualize the comparative performance and
accuracy of different forecasting methods. Furthermore, this paper presents
real application examples with natural time series datasets (i.e., wind speed
and solar radiation) to exhibit the features of the ForecastTB package to
evaluate forecasting comparison analysis as affected by the characteristics of
a dataset. Modeling results indicated the applicability and robustness of the
proposed R package ForecastTB for time series forecasting.
