Anomaly detection in time-series

For a client we developed tailor-made algorithms for anomaly detection in air and hydrostatic pressure time-series. These algorithms were implemented in a R package (gwloggeR), and made publicly available on github. A website was made for algorithm and user documentation.

To make the results understandable, the algorithms also output diagnostic plots such as these:

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