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Abstract

Historical processes manifest remarkable diversity. Nevertheless, scholars have long attempted, with some success, to identify patterns and categorize historical actors and influences. A stochastic process framework provides a structured approach for the analysis of large historical datasets that allows for detection of sometimes surprising patterns, identification of relevant causal actors both endogenous and exogenous to the process, and comparison between different historical cases. The combination of data, analytical tools and the organizing theoretical framework of stochastic processes complements traditional narrative approaches in history and archaeology.

 

Publisher’s Note: A correction article relating to this paper has been published and can be found at https://journal.caa-international.org/articles/10.5334/jcaa.164.

DOI: https://doi.org/10.5334/jcaa.113 | Journal eISSN: 2514-8362
Language: English
Submitted on: May 6, 2023
Accepted on: Nov 21, 2023
Published on: Feb 8, 2024
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2024 David H. Wolpert, Michael H. Price, Stefani A. Crabtree, Timothy A. Kohler, Jürgen Jost, James Evans, Peter F. Stadler, Hajime Shimao, Manfred D. Laubichler, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.