  Historical processes manifest remarkable diversity. Nevertheless, scholars
have long attempted to identify patterns and categorize historical actors and
influences with some success. 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.
