Estimating the Effect of Endogenous Spatial Dependency with a Hierarchical Bayesian CAR Model on Archaeological Site Location Data
This is an abstract from the "Novel Statistical Techniques in Archaeology II (QUANTARCH II)" session, at the 84th annual meeting of the Society for American Archaeology.
This research presents a method to test the endogenous spatial correlation effect when modeling the landscape sensitivity for archaeological sites. The effects of endogenous spatial correlation are inferred using a Hierarchical Bayesian model with an Conditional Auto-Regressive (CAR) component to better understand the importance of modeling spatial cultural process. In current practice, effects of endogenous spatial autocorrelation are rarely explicitly incorporated into quantitative archaeological predictive models. This is due in part to the difficulties of measuring how cultural process relate across space and time, as well as accepting the assumption that geographically near sites are implicitly more related than distant sites. Typically these difficulties are side-stepped by including aspects of cultural processes as features and ignoring endogenous spatial correlation by assuming sites are spatially independent phenomena. While there are benefits to this approach, aside from convenience, the validity of either of these assumptions has not previously been tested. The approach developed here leads to better understanding the penalty for assuming spatial independence and the development of methods to model spatial cultural process
Cite this Record
Estimating the Effect of Endogenous Spatial Dependency with a Hierarchical Bayesian CAR Model on Archaeological Site Location Data. Matthew Harris, Mary Lennon. Presented at The 84th Annual Meeting of the Society for American Archaeology, Albuquerque, NM. 2019 ( tDAR id: 452315)
This Resource is Part of the Following Collections
min long: -168.574; min lat: 7.014 ; max long: -54.844; max lat: 74.683 ;
Abstract Id(s): 24799