Adepeju, M orcid.org/0000-0002-9006-4934 (2017) Testing the adequacy of a single-value Monte Carlo simulation for space-time interaction of crime. In: Gervasi, O, Murgante, B, Misra, S, Borruso, G, Torre, CM, Rocha, AMAC, Taniar, D, Apduhan, BO, Stankova, E and Cuzzocrea, A, (eds.) Lecture Notes in Computer Science. 17th International Conference on Computer Science and Its Applications (ICCSA 2017), 03-06 Jul 2017, Trieste, Italy. Springer Nature , pp. 779-786. ISBN 978-3-319-62407-5
Abstract
The goal of this study is to determine the number of iterations (r) required in a Monte Carlo based space-time interaction analysis of crime data sets, in order to test the adequacy of using a single value of 999 iterations. A case study of burglary crime data sets is presented in which Knox test is used for the analysis of space-time interactions. The outcomes of this analysis demonstrate that the use of a single value, such as 999, does not always represent the most appropriate number of iterations especially when multiple ST neighbourhood sizes are involved. This analysis opens further research opportunities into determining the best strategy to defining the expected distribution in a space-time interaction analysis of crime.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | (c) 2017, Springer International Publishing AG. This is an author produced version of a paper published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy. The final publication is available at Springer via https://doi.org/10.1007/978-3-319-62407-5_60 |
Keywords: | Space-time neighbourhoods, Monte Carlo simulation, Crime, Knox test |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 16 Nov 2017 16:50 |
Last Modified: | 16 Jan 2018 10:01 |
Status: | Published |
Publisher: | Springer Nature |
Identification Number: | 10.1007/978-3-319-62407-5_60 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:124150 |