Citation

Gillespie CS. Ann. Appl. Stat. 2017; 11(4): 2357-2374.

Copyright

(Copyright © 2017, Institute of Mathematical Statistics)

DOI

10.1214/17-AOAS1082

PMID

unavailable

Abstract

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.

Language: en

Keywords

Bayesian; long tailed; missing data; power law