Spatio-temporal modeling to reduce women’s fear of crime

Abstract

As rape and forced indecent act crimes are increasing in Korea, fears of this are also growing. Urban experts have long recognized crime and its fear as a major challenge for sustainable cities because such things degrade the quality of life by threatening the safety of citizens. So, this research analyzes rape and forced indecent act data occurred in Seoul from 2015 to 2018 using the spatio-temporal model. For the spatio-temporal model, three types of models are considered: classical parametric, dynamic nonparametric trend, and space-time interaction nonparametric trend models. To find out how factors considered affect rape and forced indecent act crimes, the integrated nested Laplace approximation (INLA) technique based on R software is applied. This approach proposes efficient strategies to sustain women