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Lookup NU author(s): Dr Colin GillespieORCiD
This is the authors' accepted manuscript of an article that has been published in its final definitive form by Institute of Mathematical Statistics, 2017.
For re-use rights please refer to the publisher's terms and conditions.
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.
Author(s): Gillespie CS
Publication type: Article
Publication status: Published
Journal: Annals of Applied Statistics
Online publication date: 28/12/2017
Acceptance date: 04/07/2017
Date deposited: 04/10/2017
ISSN (print): 1932-6157
ISSN (electronic): 1941-7330
Publisher: Institute of Mathematical Statistics
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