The Use of Simulation-based inference methods in the Parameter Estimation of Factors Governing the Location of Known Ancient Roads

通过研究过去的运动，我们可以了解人、思想、物体和信息从一个地方到另一个地方的流动。特别是，道路提供了关于社会结构和社会如何居住的重要信息。在过去的二十年中，使用空间建模和地理信息系统来重建道路和识别控制已知道路建设的因素已经增加，特别是最小成本路径（LCP）分析，它找到了两个地理点之间的最佳路径（Hardin et al., 2012）在其应用中得到了广泛的应用。目前关于LCP在考古学中的最佳方法应用存在相当大的争论。尽管Rahn（2005）指出LCP分析代表了一种完善的方法，但Herzog（2013,184）认为这“绝不是微不足道的”，并强调仍有必要研究LCP计算中使用的参数。然而，随着模型变得越来越复杂，每个成本因素对计算的lcpp的影响变得越来越难以评估。为了克服当前LCP分析方法的局限性，并增强我们对决定道路出现和演变的因素的理解，本研究提出了基于模拟的推理方法，通过使用贝叶斯统计。贝叶斯建模方法将允许对合理支配古代道路位置的因素进行估计。

By studying past movements, we can understand the flow of people, ideas, objects, and information from place to place.In particular, roads provide important information about the structure of a society and how societies inhabited thelandscape. In the last two decades, the use of spatial modelling and Geographic Information Systems to reconstructancient roads and identify factors governing the construction of known roads has increased In particular, Least Cost Path(LCP) analysis, which finds the optimal path between two geographic points (Hardin et al., 2012) has becomewidespread in its application. There is currently considerable debate over the best methodological application of LCP inarchaeology. Though Rahn (2005) states that LCP analysis represents a well-established methodology, Herzog (2013,184) considers this by "no means trivial" and highlights that it is still necessary to investigate the parameters used withinthe LCP calculation. However, as models become more complex, the impact of each cost factor on the computed LCPbecomes more difficult to assess. To overcome the limitations in the current approach to LCP analysis and to enhanceour understanding of the factors dictating the emergence and evolution of roads, this research proposes simulation based inference methods, through the use of Bayesian statistics. The Bayesian approach to modelling will allow for theestimation of factors that plausibly governed where ancient roads were located.