ArticlePloS one2014
Fluctuation scaling, Taylor's law, and crime.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Spatial and temporal autocorrelations affect Taylor's law for US county populations: Descriptive and predictive models.PloS one · 2021Article
- A calibrated measure to compare fluctuations of different entities across timescales.Scientific reports · 2020Article
- Rural-urban scaling of age, mortality, crime and property reveals a loss of expected self-similar behaviour.Scientific reports · 2020Article
- An Urban Scaling Estimation Method in a Heterogeneity Variance Perspective.Entropy (Basel, Switzerland) · 2019Article
- Analyzing and interpreting spatial and temporal variability of the United States county population distributions using Taylor's law.PloS one · 2019Article
- Unveiling relationships between crime and property in England and Wales via density scale-adjusted metrics and network tools.PloS one · 2018Article
- The scaling of crime concentration in cities.PloS one · 2017Article
- Is this scaling nonlinear?Royal Society open science · 2016Article
- Rural to Urban Population Density Scaling of Crime and Property Transactions in English and Welsh Parliamentary Constituencies.PloS one · 2016Article
- Scale-Adjusted Metrics for Predicting the Evolution of Urban Indicators and Quantifying the Performance of Cities.PloS one · 2015Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fluctuation scaling relationships have been observed in a wide range of processes ranging from internet router traffic to measles cases. Taylor's law is one such scaling relationship and has been widely applied in ecology to understand communities including trees, birds, human populations, and insects. We show that monthly crime reports in the UK show complex fluctuation scaling which can be approximated by Taylor's law relationships corresponding to local policing neighborhoods and larger regional and countrywide scales. Regression models applied to local scale data from Derbyshire and Nottinghamshire found that different categories of crime exhibited different scaling exponents with no significant difference between the two regions. On this scale, violence reports were close to a Poisson distribution (α = 1.057 ± 0.026) while burglary exhibited a greater exponent (α = 1.292 ± 0.029) indicative of temporal clustering. These two regions exhibited significantly different pre-exponential factors for the categories of anti-social behavior and burglary indicating that local variations in crime reports can be assessed using fluctuation scaling methods. At regional and countrywide scales, all categories exhibited scaling behavior indicative of temporal clustering evidenced by Taylor's law exponents from 1.43 ± 0.12 (Drugs) to 2.094 ± 0081 (Other Crimes). Investigating crime behavior via fluctuation scaling gives insight beyond that of raw numbers and is unique in reporting on all processes contributing to the observed variance and is either robust to or exhibits signs of many types of data manipulation.
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