Sociology and Simulation: Statistical and Qualitative Cross‐Validation1
Sociology and Simulation: Statistical and Qualitative Cross‐Validation1
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社会学和模拟：统计和定性交叉验证1
DOI：
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发表时间：
2005
影响因子：
4.4
通讯作者：
B. Edmonds
中科院分区：
文献类型：
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作者：
S. Moss;B. Edmonds
基于Agent的仿真建模使正式模型的构建成为可能，这些模型可以同时针对个人行为的账户进行微观验证，并针对显示许多社会衍生时间序列特征的聚合数据进行宏观验证。这些特征（尖峰和聚集波动）有两个重要的后果：首先，它们也出现在适当结构的基于代理的模型中，就像真实的社会行为者一样，代理是社会嵌入的和亚稳定的;其次，它们的存在排除了许多标准统计技术的使用，如卡方检验。时间序列数据中的这些特征表明，合适的基于代理的模型而不是标准统计模型将是合适的。这说明了基于代理的模型的相互社会影响的生活用水需求。许多常用的统计技术的后果进行了讨论。
Agent‐based simulation modeling enables the construction of formal models that simultaneously can be microvalidated against accounts of individual behavior and macrovalidated against aggregate data that show the characteristics of many socially derived time series. These characteristics (leptokurtosis and clustered volatility) have two important consequences: first, they also appear in suitably structured agent‐based models where, like real social actors, agents are socially embedded and metastable; second, their presence precludes the use of many standard statistical techniques like the chi‐square test. These characteristics in time‐series data indicate that a suitable agent‐based model rather than a standard statistical model will be appropriate. This is illustrated with an agent‐based model of mutual social influence on domestic water demand. The consequences for many frequently used statistical techniques are discussed.
DOI：
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发表时间：
2007
期刊：
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影响因子：
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作者：
R. Sekuler;M. Kahana
通讯作者：
R. Sekuler;M. Kahana