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This article revisits an analysis on inaccuracies of time series averagingunder dynamic time warping conducted by \cite{Niennattrakul2007}. The authorspresented a correctness-criterion and introduced drift-outs of averages fromclusters. They claimed that averages are inaccurate if they are incorrect ordrift-outs. Furthermore, they conjectured that such inaccuracies are caused bythe lack of triangle inequality. We show that a rectified version of thecorrectness-criterion is unsatisfiable and that the concept of drift-out isgeometrically and operationally inconclusive. Satisfying the triangleinequality is insufficient to achieve correctness and unnecessary to overcomethe drift-out phenomenon. We place the concept of drift-out on a principledbasis and show that sample means as global minimizers of a Fr\'echet functionnever drift out. The adjusted drift-out is a way to test to which extent anapproximation is coherent. Empirical results show that solutions obtained bythe state-of-the-art methods SSG and DBA are incoherent approximations of asample mean in over a third of all trials.

Revisiting Inaccuracies of Time Series Averaging under Dynamic Time Warping