Bayesian Structural Time Series and Geographically Weighted Logistic Regression Modelling Impacts of COVID-19 Lockdowns on the Spatiotemporal Patterns of London’s Crimes

Bayesian Structural Time Series and Geographically Weighted Logistic Regression Modelling Impacts of COVID-19 Lockdowns on the Spatiotemporal Patterns of London’s Crimes

Given the paramount impacts of COVID-19 on people’s lives in the capital of the UK, London, it was foreseeable that the city’s crime patterns would have undergone significant transformations, especially during lockdown periods. This study aims to testify the crime patterns’ changes in London, using...

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Bibliographic Details
Main Authors: Rui Wang, Yijing Li
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:ISPRS International Journal of Geo-Information
Subjects:
COVID-19
lockdown
crime pattern
spatiotemporal analysis
Bayesian structural time series (BSTS)
regression
Online Access:https://www.mdpi.com/2220-9964/13/1/18

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