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Spatio-temporal modeling to reduce women's fear of crime
Journal of the Korean Data & Information Science Society 2022;33:299-309
Published online March 31, 2022;  https://doi.org/10.7465/jkdi.2022.33.2.299
© 2022 Korean Data and Information Science Society.

Young Eun Jeon1 · Suk-Bok Kang2 · Jung-In Seo3 · Joon Jin Song4

12Department of Statistics, Yeungnam University
3Department of Information Statistics, Andong National University
4Department of Statistical Science, Baylor University
Correspondence to: 1 Graduate student, Department of Statistics, Yeungnam University, Gyeongsan 38541, Korea.
2 Professor, Department of Statistics, Yeungnam University, Gyeongsan 38541, Korea.
3 Assistant professor, Department of Information Statistics, Andong National University, Andong 36729, Korea. E-mail : leehoo1928@gmail.com
4 Associate professor, Department of Statistical Science, Baylor University, One Bear Place, Waco, Texas 76798 USA.
This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2021S1A5A8063350).
Received January 6, 2022; Revised January 20, 2022; Accepted January 21, 2022.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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's safe everyday living, analyzing important risk factors affecting rape and forced indecent act crimes and the relative risk of each region.
Keywords : Forced indecent act, INLA, risk factor, spatio-temporal model.