  Recent paper "TVOR: Finding Discrete Total Variation Outliers Among
Histograms" [arXiv:2012.11574] introduces the Total Variation Outlier
Recognizer (TVOR) method for identification of outliers among a given set of
histograms. After providing a theoretical discussion of the method and
verifying its success on synthetic and population census data, it applies the
TVOR model to histograms of ages of Holocaust victims produced using United
States Holocaust Memorial Museum data. It purports to identify the list of
victims of the Jasenovac concentration camp as potentially suspicious. In this
comment paper, we show that the TVOR model and its assumptions are grossly
inapplicable to the considered dataset. When applied to the considered data,
the model is biased in assigning a higher outlier score to histograms of larger
sizes, the set of data points is extremely sparse around the point of interest,
the dataset has not been reviewed to remove obvious data processing errors,
and, contrary to the model requirements, the distributions of the victims' ages
naturally vary significantly across victim lists.
