Measurement error models for spatial network lattice data: Analysis of car crashes in Leeds
提出一个贝叶斯模型，在分析道路网络格点级别的车祸发生情况时，考虑空间协变量的测量误差，并以英国利兹市2011-2019年数据为例进行验证。
Abstract Road casualties represent an alarming concern for modern societies. During the last years, several authors proposed sophisticated approaches to help authorities implement new policies. These models were usually developed considering a set of socio-economic variables and ignoring the measurement error, which can bias the statistical inference. This paper presents a Bayesian model to analyse car crash occurrences at the network-lattice level, taking into account measurement error in the spatial covariate. The suggested methodology is exemplified by considering the collisions in the road network of Leeds (UK) during 2011–2019. Traffic volumes are approximated using an extensive set of counts obtained from mobile devices and the estimates are adjusted using a spatial measurement error correction.