Statistical analysis of spatially homogeneous dynamic agent-based processes using functional time series analysis

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• 作者：Jack D. Hywood^a ; ^{jhyw1620@uni.sydney.edu.au" class="auth_mail" title="E-mail the corresponding author} ; Mark N. Read^b ; Gregory Rice^c
• 关键词：Agent-based processes ; Agent-based models ; Functional time series ; Moment dynamics ; Spatio-temporal point process ; Spatial statistics
• 刊名：Spatial Statistics
• 出版年：2016
• 出版时间：August 2016
• 年：2016
• 卷：17
• 期：Complete
• 页码：199-219
• 全文大小：879 K

文摘

Dynamic systems consisting of multiple interacting autonomous individuals are of particular interest in a number of scientific fields, including ecology, biology, and swarm robotics. Such systems are commonly referred to as agent-based processes. Detection and characterisation of agent–agent interactions is an important step in the analysis of agent-based processes, however existing statistical methods are relatively limited. This paper presents a novel framework for investigating spatial interactions between agents combining techniques from spatial statistics and functional time series analysis. Assuming second order spatial equilibrium of the agent-based process, we develop a test for identifying the specific nature of interactions between agents. We also consider methodology for validating the assumption of spatial equilibrium for a given realisation of the agent-based process. The efficacy of this methodology is demonstrated via Monte Carlo simulation studies and an application to experimental data obtained by observing a species of flightless locust.