GeoWeightedModel: An R-Shiny package for geographically weighted models

Bibliographic Details
Main Author: De la Hoz-M, Javier
Publication Date: 2022
Other Authors: Mendes, Susana, Fernandez-Gómez, María José
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.8/8723
Summary: This paper describes GeoWeightedModel, a R package, which provides a graphical user friendly web pplication to perform techniques from a subarea of spatial Statistics known as Geographically Weighted (GW) models, such as Geographically Weighted Regression (GWR) and its extensions: Robust GWR, Generalized GWR, Heteroskedastic GWR, Mixed GWR, and ‘‘Scalable GWR), Geographically Weighted Principal Component Analysis, and Geographically Weighted Discriminant analysis. It also allows calculating a basic and robust Geographically weighted summary. The main goal of GeoWeightedModel package was to make the workflow easier to use, especially for those who are not familiar with the R environment. With GeoWeightedModel, analyses can be performed interactively (point-and-click way) in a web browser, making the applications easier for many more researchers. In addition with this tool, the results of the analyses can be mapped providing a valuable tool for exploring the spatial heterogeneity of the data.
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spelling GeoWeightedModel: An R-Shiny package for geographically weighted modelsGeographically weightedGeographically weighted analysisSpatial heterogeneityGeographically weighted regressionGeographically weighted principal component analysisDiscriminant geographically weighted analysisThis paper describes GeoWeightedModel, a R package, which provides a graphical user friendly web pplication to perform techniques from a subarea of spatial Statistics known as Geographically Weighted (GW) models, such as Geographically Weighted Regression (GWR) and its extensions: Robust GWR, Generalized GWR, Heteroskedastic GWR, Mixed GWR, and ‘‘Scalable GWR), Geographically Weighted Principal Component Analysis, and Geographically Weighted Discriminant analysis. It also allows calculating a basic and robust Geographically weighted summary. The main goal of GeoWeightedModel package was to make the workflow easier to use, especially for those who are not familiar with the R environment. With GeoWeightedModel, analyses can be performed interactively (point-and-click way) in a web browser, making the applications easier for many more researchers. In addition with this tool, the results of the analyses can be mapped providing a valuable tool for exploring the spatial heterogeneity of the data.ElsevierRepositório IC-OnlineDe la Hoz-M, JavierMendes, SusanaFernandez-Gómez, María José2023-08-23T10:29:40Z20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.8/8723eng2352-711010.1016/j.softx.2022.101250info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-25T15:19:58Zoai:iconline.ipleiria.pt:10400.8/8723Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T20:58:48.979032Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv GeoWeightedModel: An R-Shiny package for geographically weighted models
title GeoWeightedModel: An R-Shiny package for geographically weighted models
spellingShingle GeoWeightedModel: An R-Shiny package for geographically weighted models
De la Hoz-M, Javier
Geographically weighted
Geographically weighted analysis
Spatial heterogeneity
Geographically weighted regression
Geographically weighted principal component analysis
Discriminant geographically weighted analysis
title_short GeoWeightedModel: An R-Shiny package for geographically weighted models
title_full GeoWeightedModel: An R-Shiny package for geographically weighted models
title_fullStr GeoWeightedModel: An R-Shiny package for geographically weighted models
title_full_unstemmed GeoWeightedModel: An R-Shiny package for geographically weighted models
title_sort GeoWeightedModel: An R-Shiny package for geographically weighted models
author De la Hoz-M, Javier
author_facet De la Hoz-M, Javier
Mendes, Susana
Fernandez-Gómez, María José
author_role author
author2 Mendes, Susana
Fernandez-Gómez, María José
author2_role author
author
dc.contributor.none.fl_str_mv Repositório IC-Online
dc.contributor.author.fl_str_mv De la Hoz-M, Javier
Mendes, Susana
Fernandez-Gómez, María José
dc.subject.por.fl_str_mv Geographically weighted
Geographically weighted analysis
Spatial heterogeneity
Geographically weighted regression
Geographically weighted principal component analysis
Discriminant geographically weighted analysis
topic Geographically weighted
Geographically weighted analysis
Spatial heterogeneity
Geographically weighted regression
Geographically weighted principal component analysis
Discriminant geographically weighted analysis
description This paper describes GeoWeightedModel, a R package, which provides a graphical user friendly web pplication to perform techniques from a subarea of spatial Statistics known as Geographically Weighted (GW) models, such as Geographically Weighted Regression (GWR) and its extensions: Robust GWR, Generalized GWR, Heteroskedastic GWR, Mixed GWR, and ‘‘Scalable GWR), Geographically Weighted Principal Component Analysis, and Geographically Weighted Discriminant analysis. It also allows calculating a basic and robust Geographically weighted summary. The main goal of GeoWeightedModel package was to make the workflow easier to use, especially for those who are not familiar with the R environment. With GeoWeightedModel, analyses can be performed interactively (point-and-click way) in a web browser, making the applications easier for many more researchers. In addition with this tool, the results of the analyses can be mapped providing a valuable tool for exploring the spatial heterogeneity of the data.
publishDate 2022
dc.date.none.fl_str_mv 2022
2022-01-01T00:00:00Z
2023-08-23T10:29:40Z
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 http://hdl.handle.net/10400.8/8723
url http://hdl.handle.net/10400.8/8723
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2352-7110
10.1016/j.softx.2022.101250
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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