Time Series Forecasting Using Independent Component Analysis

Theodor D. Popescu
2009 Zenodo  
The paper presents a method for multivariate time series forecasting using Independent Component Analysis (ICA), as a preprocessing tool. The idea of this approach is to do the forecasting in the space of independent components (sources), and then to transform back the results to the original time series space. The forecasting can be done separately and with a different method for each component, depending on its time structure. The paper gives also a review of the main algorithms for
more » ... t component analysis in the case of instantaneous mixture models, using second and high-order statistics. The method has been applied in simulation to an artificial multivariate time series with five components, generated from three sources and a mixing matrix, randomly generated.
doi:10.5281/zenodo.1074779 fatcat:x2fv4zgetrc25n3zv7okbjequu