Publicação
GeoWeightedModel: An R-Shiny package for geographically weighted models
| dc.contributor.author | De la Hoz-M, Javier | |
| dc.contributor.author | Mendes, Susana | |
| dc.contributor.author | Fernandez-Gómez, María José | |
| dc.date.accessioned | 2023-08-23T10:29:40Z | |
| dc.date.available | 2023-08-23T10:29:40Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | 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. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | Javier De La Hoz-M, Susana Mendes, María José Fernandez-Gómez, GeoWeightedModel : An R-Shiny package for Geographically Weighted Models, SoftwareX, Volume 20, 2022, 101250, ISSN 2352-7110, https://doi.org/10.1016/j.softx.2022.101250 | pt_PT |
| dc.identifier.doi | 10.1016/j.softx.2022.101250 | pt_PT |
| dc.identifier.issn | 2352-7110 | |
| dc.identifier.uri | http://hdl.handle.net/10400.8/8723 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | Elsevier | pt_PT |
| dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S2352711022001686 | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Geographically weighted | pt_PT |
| dc.subject | Geographically weighted analysis | pt_PT |
| dc.subject | Spatial heterogeneity | pt_PT |
| dc.subject | Geographically weighted regression | pt_PT |
| dc.subject | Geographically weighted principal component analysis | pt_PT |
| dc.subject | Discriminant geographically weighted analysis | pt_PT |
| dc.title | GeoWeightedModel: An R-Shiny package for geographically weighted models | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.title | SoftwareX | pt_PT |
| oaire.citation.volume | 20 | pt_PT |
| person.familyName | DE LA HOZ-M | |
| person.familyName | Mendes | |
| person.givenName | JAVIER | |
| person.givenName | Susana | |
| person.identifier | 322266 | |
| person.identifier.ciencia-id | 4514-12E2-1FD9 | |
| person.identifier.orcid | 0000-0001-7779-0803 | |
| person.identifier.orcid | 0000-0001-9681-3169 | |
| person.identifier.scopus-author-id | 34976470100 | |
| person.identifier.scopus-author-id | 33568138000 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
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