Forecasting the number of vehicles thefts in Campinas
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://repositorio.ufla.br/jspui/handle/1/55192 |
Resumo: | By definition, thefts are considered the act of taking away other people’s mobile possessions for personal use or for others, affecting crime rates, economic indicators and enabling recent studies to create risk zones in society, contributing to insurance pricing in actuarial methods. This paper analyzes the number of vehicle thefts of 38 locations near Campinas/S˜ao Paulo, Brazil, using a GLARMA(p,q) model with Poisson and Negative Binomial response. The main feature of GLARMA(p,q) is to consider the peculiarities of counting data as high dispersion. As a result, it was possible to verify the adequacy and usefulness of the model for counting data. With specific techniques for estimating time series related to the public security area, patterns can be better understood, revealing relevant information that can be added to decision-making processes to direct public policies. |
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Forecasting the number of vehicles thefts in CampinasBrazil using a generalized linear autoregressive moving average modelCtuaryGlarma modelVehicles theftsPublic policiesBy definition, thefts are considered the act of taking away other people’s mobile possessions for personal use or for others, affecting crime rates, economic indicators and enabling recent studies to create risk zones in society, contributing to insurance pricing in actuarial methods. This paper analyzes the number of vehicle thefts of 38 locations near Campinas/S˜ao Paulo, Brazil, using a GLARMA(p,q) model with Poisson and Negative Binomial response. The main feature of GLARMA(p,q) is to consider the peculiarities of counting data as high dispersion. As a result, it was possible to verify the adequacy and usefulness of the model for counting data. With specific techniques for estimating time series related to the public security area, patterns can be better understood, revealing relevant information that can be added to decision-making processes to direct public policies.Università del Salento2022-09-23T21:29:41Z2022-09-23T21:29:41Z2022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfPALA, L. O. de O.; CARVALHO, M. de M.; SÁFADI, T. Forecasting the number of vehicles thefts in Campinas. Electronic Journal of Applied Statistical Analysis, [S. l.], v. 15, n. 1, p. 110-122, May 2022. DOI: 10.1285/i20705948v15n1p110.http://repositorio.ufla.br/jspui/handle/1/55192Electronic Journal of Applied Statistical Analysisreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessPala, Luiz Otávio de OliveiraCarvalho, Marcela de MarillacSáfadi, Thelmaeng2023-05-26T19:36:50Zoai:localhost:1/55192Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2023-05-26T19:36:50Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Forecasting the number of vehicles thefts in Campinas Brazil using a generalized linear autoregressive moving average model |
title |
Forecasting the number of vehicles thefts in Campinas |
spellingShingle |
Forecasting the number of vehicles thefts in Campinas Pala, Luiz Otávio de Oliveira Ctuary Glarma model Vehicles thefts Public policies |
title_short |
Forecasting the number of vehicles thefts in Campinas |
title_full |
Forecasting the number of vehicles thefts in Campinas |
title_fullStr |
Forecasting the number of vehicles thefts in Campinas |
title_full_unstemmed |
Forecasting the number of vehicles thefts in Campinas |
title_sort |
Forecasting the number of vehicles thefts in Campinas |
author |
Pala, Luiz Otávio de Oliveira |
author_facet |
Pala, Luiz Otávio de Oliveira Carvalho, Marcela de Marillac Sáfadi, Thelma |
author_role |
author |
author2 |
Carvalho, Marcela de Marillac Sáfadi, Thelma |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Pala, Luiz Otávio de Oliveira Carvalho, Marcela de Marillac Sáfadi, Thelma |
dc.subject.por.fl_str_mv |
Ctuary Glarma model Vehicles thefts Public policies |
topic |
Ctuary Glarma model Vehicles thefts Public policies |
description |
By definition, thefts are considered the act of taking away other people’s mobile possessions for personal use or for others, affecting crime rates, economic indicators and enabling recent studies to create risk zones in society, contributing to insurance pricing in actuarial methods. This paper analyzes the number of vehicle thefts of 38 locations near Campinas/S˜ao Paulo, Brazil, using a GLARMA(p,q) model with Poisson and Negative Binomial response. The main feature of GLARMA(p,q) is to consider the peculiarities of counting data as high dispersion. As a result, it was possible to verify the adequacy and usefulness of the model for counting data. With specific techniques for estimating time series related to the public security area, patterns can be better understood, revealing relevant information that can be added to decision-making processes to direct public policies. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-09-23T21:29:41Z 2022-09-23T21:29:41Z 2022 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
PALA, L. O. de O.; CARVALHO, M. de M.; SÁFADI, T. Forecasting the number of vehicles thefts in Campinas. Electronic Journal of Applied Statistical Analysis, [S. l.], v. 15, n. 1, p. 110-122, May 2022. DOI: 10.1285/i20705948v15n1p110. http://repositorio.ufla.br/jspui/handle/1/55192 |
identifier_str_mv |
PALA, L. O. de O.; CARVALHO, M. de M.; SÁFADI, T. Forecasting the number of vehicles thefts in Campinas. Electronic Journal of Applied Statistical Analysis, [S. l.], v. 15, n. 1, p. 110-122, May 2022. DOI: 10.1285/i20705948v15n1p110. |
url |
http://repositorio.ufla.br/jspui/handle/1/55192 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Università del Salento |
publisher.none.fl_str_mv |
Università del Salento |
dc.source.none.fl_str_mv |
Electronic Journal of Applied Statistical Analysis reponame:Repositório Institucional da UFLA instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Repositório Institucional da UFLA |
collection |
Repositório Institucional da UFLA |
repository.name.fl_str_mv |
Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
nivaldo@ufla.br || repositorio.biblioteca@ufla.br |
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1784550086893633536 |