Zero-inflated-censored Weibull and gamma regression models to estimate wild boar population dispersal distance
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/248346 |
Resumo: | The dynamics of the wild boar population has become a pressing issue not only for ecological purposes, but also for agricultural and livestock production. The data related to the wild boar dispersal distance can have a complex structure, including excess of zeros and right-censored observations, thus being challenging for modeling. In this sense, we propose two different zero-inflated-right-censored regression models, assuming Weibull and gamma distributions. First, we present the construction of the likelihood function, and then, we apply both models to simulated datasets, demonstrating that both regression models behave well. The simulation results point to the consistency and asymptotic unbiasedness of the developed methods. Afterwards, we adjusted both models to a simulated dataset of wild boar dispersal, including excess of zeros, right-censored observations, and two covariates: age and sex. We showed that the models were useful to extract inferences about the wild boar dispersal, correctly describing the data mimicking a situation where males disperse more than females, and age has a positive effect on the dispersal of the wild boars. These results are useful to overcome some limitations regarding inferences in zero-inflated-right-censored datasets, especially concerning the wild boar’s population. Users will be provided with an R function to run the proposed models. |
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Costa, Eduardo de FreitasSchneider, SilvanaCarlotto, Giulia BagatiniCabalheiro, Tainá FerreiraOliveira Júnior, Mauro Ribeiro de2022-08-31T04:56:29Z20212520-8764http://hdl.handle.net/10183/248346001148523The dynamics of the wild boar population has become a pressing issue not only for ecological purposes, but also for agricultural and livestock production. The data related to the wild boar dispersal distance can have a complex structure, including excess of zeros and right-censored observations, thus being challenging for modeling. In this sense, we propose two different zero-inflated-right-censored regression models, assuming Weibull and gamma distributions. First, we present the construction of the likelihood function, and then, we apply both models to simulated datasets, demonstrating that both regression models behave well. The simulation results point to the consistency and asymptotic unbiasedness of the developed methods. Afterwards, we adjusted both models to a simulated dataset of wild boar dispersal, including excess of zeros, right-censored observations, and two covariates: age and sex. We showed that the models were useful to extract inferences about the wild boar dispersal, correctly describing the data mimicking a situation where males disperse more than females, and age has a positive effect on the dispersal of the wild boars. These results are useful to overcome some limitations regarding inferences in zero-inflated-right-censored datasets, especially concerning the wild boar’s population. Users will be provided with an R function to run the proposed models.application/pdfengJapanese Journal of Statistics and Data Science (JJSD). Jpn J Stat Data Sci. Vol. 4, num. 2,. Japan, Japanese Federation of Statistical Science Associations (JFSSA), Dec. 2021. p. 1133–1155Estatística aplicadaModelos estatísticosZero-inflated-censored Weibull and gamma regression models to estimate wild boar population dispersal distanceEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001148523.pdf.txt001148523.pdf.txtExtracted Texttext/plain56914http://www.lume.ufrgs.br/bitstream/10183/248346/2/001148523.pdf.txt14028175305e67524dbc58160db96b99MD52ORIGINAL001148523.pdfTexto completo (inglês)application/pdf2432584http://www.lume.ufrgs.br/bitstream/10183/248346/1/001148523.pdfe5cc4832a6ae68fe1bfbfb7dd9fc3d9eMD5110183/2483462022-09-01 04:58:56.889614oai:www.lume.ufrgs.br:10183/248346Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2022-09-01T07:58:56Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Zero-inflated-censored Weibull and gamma regression models to estimate wild boar population dispersal distance |
title |
Zero-inflated-censored Weibull and gamma regression models to estimate wild boar population dispersal distance |
spellingShingle |
Zero-inflated-censored Weibull and gamma regression models to estimate wild boar population dispersal distance Costa, Eduardo de Freitas Estatística aplicada Modelos estatísticos |
title_short |
Zero-inflated-censored Weibull and gamma regression models to estimate wild boar population dispersal distance |
title_full |
Zero-inflated-censored Weibull and gamma regression models to estimate wild boar population dispersal distance |
title_fullStr |
Zero-inflated-censored Weibull and gamma regression models to estimate wild boar population dispersal distance |
title_full_unstemmed |
Zero-inflated-censored Weibull and gamma regression models to estimate wild boar population dispersal distance |
title_sort |
Zero-inflated-censored Weibull and gamma regression models to estimate wild boar population dispersal distance |
author |
Costa, Eduardo de Freitas |
author_facet |
Costa, Eduardo de Freitas Schneider, Silvana Carlotto, Giulia Bagatini Cabalheiro, Tainá Ferreira Oliveira Júnior, Mauro Ribeiro de |
author_role |
author |
author2 |
Schneider, Silvana Carlotto, Giulia Bagatini Cabalheiro, Tainá Ferreira Oliveira Júnior, Mauro Ribeiro de |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Costa, Eduardo de Freitas Schneider, Silvana Carlotto, Giulia Bagatini Cabalheiro, Tainá Ferreira Oliveira Júnior, Mauro Ribeiro de |
dc.subject.por.fl_str_mv |
Estatística aplicada Modelos estatísticos |
topic |
Estatística aplicada Modelos estatísticos |
description |
The dynamics of the wild boar population has become a pressing issue not only for ecological purposes, but also for agricultural and livestock production. The data related to the wild boar dispersal distance can have a complex structure, including excess of zeros and right-censored observations, thus being challenging for modeling. In this sense, we propose two different zero-inflated-right-censored regression models, assuming Weibull and gamma distributions. First, we present the construction of the likelihood function, and then, we apply both models to simulated datasets, demonstrating that both regression models behave well. The simulation results point to the consistency and asymptotic unbiasedness of the developed methods. Afterwards, we adjusted both models to a simulated dataset of wild boar dispersal, including excess of zeros, right-censored observations, and two covariates: age and sex. We showed that the models were useful to extract inferences about the wild boar dispersal, correctly describing the data mimicking a situation where males disperse more than females, and age has a positive effect on the dispersal of the wild boars. These results are useful to overcome some limitations regarding inferences in zero-inflated-right-censored datasets, especially concerning the wild boar’s population. Users will be provided with an R function to run the proposed models. |
publishDate |
2021 |
dc.date.issued.fl_str_mv |
2021 |
dc.date.accessioned.fl_str_mv |
2022-08-31T04:56:29Z |
dc.type.driver.fl_str_mv |
Estrangeiro info:eu-repo/semantics/article |
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article |
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2520-8764 |
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001148523 |
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http://hdl.handle.net/10183/248346 |
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eng |
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dc.relation.ispartof.pt_BR.fl_str_mv |
Japanese Journal of Statistics and Data Science (JJSD). Jpn J Stat Data Sci. Vol. 4, num. 2,. Japan, Japanese Federation of Statistical Science Associations (JFSSA), Dec. 2021. p. 1133–1155 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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