  The American Indian war lasted over one hundred years, and is a major event
in the history of North America. As expected, since the war commenced in late
eighteenth century, casualty records surrounding this conflict contain numerous
sources of error, such as rounding and counting. Additionally, while major
battles such as the Battle of the Little Bighorn were recorded, many smaller
skirmishes were completely omitted from the records. Over the last few decades,
it has been observed that the number of casualties in major conflicts follows a
power law distribution. This paper places this observation within the Bayesian
paradigm, enabling modelling of different error sources, allowing inferences to
be made about the overall casualty numbers in the American Indian war.
