Corpus ID: 27930575

Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast Tasks

@inproceedings{Gregorov2017LearningPL,
  title={Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast Tasks},
  author={Magda Gregorov{\'a} and Alexandros Kalousis and St{\'e}phane Marchand-Maillet},
  booktitle={ACML},
  year={2017}
}
We present a new method for forecasting systems of multiple interrelated time series. The method learns the forecast models together with discovering leading indicators from within the system that serve as good predictors improving the forecast accuracy and a cluster structure of the predictive tasks around these. The method is based on the classical linear vector autoregressive model (VAR) and links the discovery of the leading indicators to inferring sparse graphs of Granger causality. We… 
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