George E. Tita

TL;DR: The implementation of self-exciting point process models in the context of urban crime is illustrated using residential burglary data provided by the Los Angeles Police Department to gain insight into the form of the space–time triggering function and temporal trends in the background rate of burglary.

TL;DR: This work focuses on a two-dimensional lattice model for residential burglary, where each site is characterized by a dynamic attractiveness variable, and where each criminal is represented as a random walker.

TL;DR: In this paper, a new method for examining dynamic changes in the spatial distribution of a phenomenon is proposed, which is based on exploratory spatial data analysis (ESDA) techniques.

TL;DR: Examination of the most recently available data from both Los Angeles, CA, and Indianapolis, IN, shows that social distancing has had a statistically significant impact on a few specific crime types, however, the overall effect is notably less than might be expected given the scale of the disruption to social and economic life.

TL;DR: In this article, the authors report results of two randomized controlled trials of near real-time epidemic-type aftershock sequence (ETAS) crime forecasting, one trial within three divisions of the Los Angeles Police Department and the other trial within two divisions of Kent Police Department (United Kingdom).