  This technical report tries to fill a gap in current literature on Timescale
Graphical Event Models. I propose and evaluate different heuristics to
determine hyper-parameters during the structure learning algorithm and refine
an existing distance measure. A comprehensive benchmark on synthetic data will
be conducted allowing conclusions about the applicability of the different
heuristics.
