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Extremal Event Graphs: A (Stable) Tool for Analyzing Noisy Time Series Data
[article]
2022
arXiv
pre-print
Local maxima and minima, or extremal events, in experimental time series can be used as a coarse summary to characterize data. However, the discrete sampling in recording experimental measurements suggests uncertainty on the true timing of extrema during the experiment. This in turn gives uncertainty in the timing order of extrema within the time series. Motivated by applications in genomic time series and biological network analysis, we construct a weighted directed acyclic graph (DAG) called
arXiv:2203.09552v3
fatcat:mmherivncbffba2be7zocghqlq