Metric adaption for analog forecasting

The performance of analog forecasts is sensitive to the selection procedure of analogs from the history of observed time series. A method is presented to iteratively reduce a user-defined forecast error measure by adapting suitable metric weights for the components of the reconstructed states to be selected. Applications of the adapted analog forecast scheme to time series generated by low-dimensional systems demonstrate successfully the potential of the proposed technique.