Presentation
Burglary Crime Analysis Using Logistic Regression
15th International Conference on Human Interface and the Management of Information / Human-Computer Interaction, published in in S. Yamamoto (Ed.): HIMI/HCII 2013, Part III, LNCS 8018, pp. 549--558. Springer, Heidelberg
(2013)
Abstract
This study used a logistic regression model to investigate the relationship between several predicting factors and burglary occurrence probability with regard to the epicenter. These factors include day of the week, time of the day, repeated victimization, connectors and barriers. Data was collected from a local police report on 2010 burglary incidents. Results showed the model has various degrees of significance in terms of predicting the occurrence within difference ranges from the epicenter. Follow-up refined multiple comparisons of different sizes were observed to further discover the pattern of prediction strength of these factors. Results are discussed and further research directions were given at the end of the paper.
Keywords
- Human decision making,
- small worlds,
- social science,
- burglary studies
Disciplines
Publication Date
July 21, 2013
Comments
Part of Lecture Notes in Computer Science book series, volume 8018.
Citation Information
Daniel Antolos, Dahai Liu, Andrei Ludu and Dennis Vincenzi. "Burglary Crime Analysis Using Logistic Regression" 15th International Conference on Human Interface and the Management of Information / Human-Computer Interaction, published in in S. Yamamoto (Ed.): HIMI/HCII 2013, Part III, LNCS 8018, pp. 549--558. Springer, Heidelberg (2013) Available at: http://works.bepress.com/andrei_ludu/17/