A framework for dynamically combining forecasting models for time series forecasting predictive tasks. It leverages machine learning models from other packages to automatically combine expert advice using metalearning and other state-of-the-art forecasting combination approaches. The predictive methods receive a data matrix as input, representing an embedded time series, and return a predictive ensemble model. The ensemble use generic functions 'predict()' and 'forecast()' to forecast future ...

Latest Versions

7 versions โ†’
VersionVulnerabilitiesUsagesDate
0.0.x
0.0.3-b1
0
Apr 30, 2022
0.0.2-b9
0
Apr 30, 2022
0.0.2-b8
0
Apr 30, 2022
7 versions โ†’