Multi-level statistical analysis of high-frequency spatio-temporal process data (C03)

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High-frequency high-dimensional process data are typically analyzed in several steps. Interesting data need to be identified and selected in real time for further analysis because of limited storage capacities. By means of the challenging example of detection and classification of astrophysical particles appearing as transient patterns in spatio-temporal data, we want to construct robust generalizable techniques for reduction, classification, and modeling of such data, as well as strategies for the suitable combination of these analysis steps.