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首页> 外文期刊>Transactions in GIS: TG >Monitoring Residual Spatial Patterns using Bayesian Hierarchical Spatial Modelling for Exploring Unknown Risk Factors
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Monitoring Residual Spatial Patterns using Bayesian Hierarchical Spatial Modelling for Exploring Unknown Risk Factors

机译：使用贝叶斯分层空间模型监控残留空间模式以探索未知的风险因素

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摘要

This article studies Bayesian hierarchical spatial modelling that monitors the changes of residual spatial pattern (structure) of the outcome variable for exploring unknown risk factors in small-area analysis. Spatially structured random effects (SRE) and unstructured random effects (URE) terms added to the conventional logistic regression model take into account overdispersion and residual spatial structure, which if unaccounted for could cause incorrect identification of risk factors. Mapping and/or calculating the ratio of random effects that are spatially-structured monitor the extent of residual spatial structure. The monitoring provides insights into identification of unknown covariates that have similar spatial structures to those of SRE. Adding such covariates to the model has the potential to diminish the residual spatial structure, until possibly all or most of the spatial structure can be explained. Risk factors identified are the added covariates that have statistically significant regression coefficients. We apply the methods to the analysis of domestic burglaries in Cambridgeshire, England. Small-area analysis of crime where data often display apparent spatial structure would particularly benefit from the methodologies. We discuss the methodologies, their relevancy in our analysis of domestic burglaries, their limitations, and possible paths for future research.
机译：本文研究贝叶斯分层空间模型，该模型监视结果变量的剩余空间模式（结构）的变化，以探索小面积分析中的未知风险因素。常规逻辑回归模型中添加的空间结构随机效应（SRE）和非结构随机效应（URE）术语考虑了过度分散和剩余空间结构，如果不加以考虑，则可能导致对危险因素的错误识别。映射和/或计算空间结构随机效应的比率可监视剩余空间结构的程度。监视提供洞察力，以识别具有与SRE相似的空间结构的未知协变量。将此类协变量添加到模型中可能会减少残留的空间结构，直到可以解释所有或大部分空间结构为止。确定的风险因素是具有统计显着性回归系数的附加协变量。我们将这些方法用于分析英国剑桥郡的家庭盗窃案。从犯罪方法进行数据的小区域分析通常会显示明显的空间结构，这将特别受益。我们将讨论方法，其在分析家庭盗窃中的相关性，其局限性以及未来研究的可能途径。

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