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In this article, a new nonparametric and robust method of forecastinghierarchical functional time series is presented. The method is compared withHyndman and Shang's method with respect to their unbiasedness, effectiveness,robustness, and computational complexity. Taking into account results of theanalytical, simulation and empirical studies, we come to the conclusion thatour proposal is superior over the proposal of Hyndman and Shang with respect tosome statistical criteria and especially with respect to robustness andcomputational complexity. An empirical usefulness of our method is presented onexample of management of a certain web portal divided into four subservices. Anextensive simulation study involving hierarchical systems consisted of FAR(1)processes and Wiener processes has been conducted as well.

Aggregated moving functional median in robust prediction of hierarchical  functional time series - an application to forecasting web portal users  behaviors