Distance to the scaling law: a useful approach for unveiling relationships between crime and urban metrics.

We report on a quantitative analysis of relationships between the number of homicides, population size and ten other urban metrics. By using data from Brazilian cities, we show that well-defined average scaling laws with the population size emerge when investigating the relations between population...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Luiz G A Alves, Haroldo V Ribeiro, Ervin K Lenzi, Renio S Mendes
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/b7cad0ce070040f9a11e252060901af4
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:b7cad0ce070040f9a11e252060901af4
record_format	dspace
spelling	oai:doaj.org-article:b7cad0ce070040f9a11e252060901af42021-11-18T09:01:26ZDistance to the scaling law: a useful approach for unveiling relationships between crime and urban metrics.1932-620310.1371/journal.pone.0069580https://doaj.org/article/b7cad0ce070040f9a11e252060901af42013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23940525/?tool=EBIhttps://doaj.org/toc/1932-6203We report on a quantitative analysis of relationships between the number of homicides, population size and ten other urban metrics. By using data from Brazilian cities, we show that well-defined average scaling laws with the population size emerge when investigating the relations between population and number of homicides as well as population and urban metrics. We also show that the fluctuations around the scaling laws are log-normally distributed, which enabled us to model these scaling laws by a stochastic-like equation driven by a multiplicative and log-normally distributed noise. Because of the scaling laws, we argue that it is better to employ logarithms in order to describe the number of homicides in function of the urban metrics via regression analysis. In addition to the regression analysis, we propose an approach to correlate crime and urban metrics via the evaluation of the distance between the actual value of the number of homicides (as well as the value of the urban metrics) and the value that is expected by the scaling law with the population size. This approach has proved to be robust and useful for unveiling relationships/behaviors that were not properly carried out by the regression analysis, such as [Formula: see text] the non-explanatory potential of the elderly population when the number of homicides is much above or much below the scaling law, [Formula: see text] the fact that unemployment has explanatory potential only when the number of homicides is considerably larger than the expected by the power law, and [Formula: see text] a gender difference in number of homicides, where cities with female population below the scaling law are characterized by a number of homicides above the power law.Luiz G A AlvesHaroldo V RibeiroErvin K LenziRenio S MendesPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 8, p e69580 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Luiz G A Alves Haroldo V Ribeiro Ervin K Lenzi Renio S Mendes Distance to the scaling law: a useful approach for unveiling relationships between crime and urban metrics.
description	We report on a quantitative analysis of relationships between the number of homicides, population size and ten other urban metrics. By using data from Brazilian cities, we show that well-defined average scaling laws with the population size emerge when investigating the relations between population and number of homicides as well as population and urban metrics. We also show that the fluctuations around the scaling laws are log-normally distributed, which enabled us to model these scaling laws by a stochastic-like equation driven by a multiplicative and log-normally distributed noise. Because of the scaling laws, we argue that it is better to employ logarithms in order to describe the number of homicides in function of the urban metrics via regression analysis. In addition to the regression analysis, we propose an approach to correlate crime and urban metrics via the evaluation of the distance between the actual value of the number of homicides (as well as the value of the urban metrics) and the value that is expected by the scaling law with the population size. This approach has proved to be robust and useful for unveiling relationships/behaviors that were not properly carried out by the regression analysis, such as [Formula: see text] the non-explanatory potential of the elderly population when the number of homicides is much above or much below the scaling law, [Formula: see text] the fact that unemployment has explanatory potential only when the number of homicides is considerably larger than the expected by the power law, and [Formula: see text] a gender difference in number of homicides, where cities with female population below the scaling law are characterized by a number of homicides above the power law.
format	article
author	Luiz G A Alves Haroldo V Ribeiro Ervin K Lenzi Renio S Mendes
author_facet	Luiz G A Alves Haroldo V Ribeiro Ervin K Lenzi Renio S Mendes
author_sort	Luiz G A Alves
title	Distance to the scaling law: a useful approach for unveiling relationships between crime and urban metrics.
title_short	Distance to the scaling law: a useful approach for unveiling relationships between crime and urban metrics.
title_full	Distance to the scaling law: a useful approach for unveiling relationships between crime and urban metrics.
title_fullStr	Distance to the scaling law: a useful approach for unveiling relationships between crime and urban metrics.
title_full_unstemmed	Distance to the scaling law: a useful approach for unveiling relationships between crime and urban metrics.
title_sort	distance to the scaling law: a useful approach for unveiling relationships between crime and urban metrics.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/b7cad0ce070040f9a11e252060901af4
work_keys_str_mv	AT luizgaalves distancetothescalinglawausefulapproachforunveilingrelationshipsbetweencrimeandurbanmetrics AT haroldovribeiro distancetothescalinglawausefulapproachforunveilingrelationshipsbetweencrimeandurbanmetrics AT ervinklenzi distancetothescalinglawausefulapproachforunveilingrelationshipsbetweencrimeandurbanmetrics AT reniosmendes distancetothescalinglawausefulapproachforunveilingrelationshipsbetweencrimeandurbanmetrics
_version_	1718421044989001728

Distance to the scaling law: a useful approach for unveiling relationships between crime and urban metrics.

Ejemplares similares