GWmodelS: A software for geographically weighted models

Spatial heterogeneity or non-stationarity has become a popular and necessary concern in exploring relationships between variables. In this regard, geographically weighted (GW) models provide a powerful collection of techniques in its quantitative description. We developed a user-friendly, high-perfo...
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Autor*in:	Binbin Lu [verfasserIn] Yigong Hu [verfasserIn] Dongyang Yang [verfasserIn] Yong Liu [verfasserIn] Liuqi Liao [verfasserIn] Zuoyao Yin [verfasserIn] Tianyang Xia [verfasserIn] Zheyi Dong [verfasserIn] Paul Harris [verfasserIn] Chris Brunsdon [verfasserIn] Lex Comber [verfasserIn] Guanpeng Dong [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Spatial heterogeneity Spatio-temporal models Visualization High-performance Local techniques

Übergeordnetes Werk:	In: SoftwareX - Elsevier, 2016, 21(2023), Seite 101291-
Übergeordnetes Werk:	volume:21 ; year:2023 ; pages:101291-

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1016/j.softx.2022.101291

Katalog-ID:	DOAJ080553591

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520			\|a Spatial heterogeneity or non-stationarity has become a popular and necessary concern in exploring relationships between variables. In this regard, geographically weighted (GW) models provide a powerful collection of techniques in its quantitative description. We developed a user-friendly, high-performance and systematic software, named GWmodelS, to promote better and broader usages of such models. Apart from a variety of GW models, including GW descriptive statistics, GW regression models, and GW principal components analysis, data management and mapping tools have also been incorporated with well-designed interfaces.
650		4	\|a Spatial heterogeneity
650		4	\|a Spatio-temporal models
650		4	\|a Visualization
650		4	\|a High-performance
650		4	\|a Local techniques
653		0	\|a Computer software
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700	0		\|a Liuqi Liao \|e verfasserin \|4 aut
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700	0		\|a Tianyang Xia \|e verfasserin \|4 aut
700	0		\|a Zheyi Dong \|e verfasserin \|4 aut
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700	0		\|a Lex Comber \|e verfasserin \|4 aut
700	0		\|a Guanpeng Dong \|e verfasserin \|4 aut
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912			\|a GBV_ILN_224
912			\|a GBV_ILN_230
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_2001
912			\|a GBV_ILN_2003
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912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2056
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
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912			\|a GBV_ILN_2088
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912			\|a GBV_ILN_2110
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912			\|a GBV_ILN_4323
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912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4326
912			\|a GBV_ILN_4333
912			\|a GBV_ILN_4334
912			\|a GBV_ILN_4335
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4367
912			\|a GBV_ILN_4393
912			\|a GBV_ILN_4700
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allfields	10.1016/j.softx.2022.101291 doi (DE-627)DOAJ080553591 (DE-599)DOAJbd32ca60bf7e4cb782b9d1a0ded18d80 DE-627 ger DE-627 rakwb eng QA76.75-76.765 Binbin Lu verfasserin aut GWmodelS: A software for geographically weighted models 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Spatial heterogeneity or non-stationarity has become a popular and necessary concern in exploring relationships between variables. In this regard, geographically weighted (GW) models provide a powerful collection of techniques in its quantitative description. We developed a user-friendly, high-performance and systematic software, named GWmodelS, to promote better and broader usages of such models. Apart from a variety of GW models, including GW descriptive statistics, GW regression models, and GW principal components analysis, data management and mapping tools have also been incorporated with well-designed interfaces. Spatial heterogeneity Spatio-temporal models Visualization High-performance Local techniques Computer software Yigong Hu verfasserin aut Dongyang Yang verfasserin aut Yong Liu verfasserin aut Liuqi Liao verfasserin aut Zuoyao Yin verfasserin aut Tianyang Xia verfasserin aut Zheyi Dong verfasserin aut Paul Harris verfasserin aut Chris Brunsdon verfasserin aut Lex Comber verfasserin aut Guanpeng Dong verfasserin aut In SoftwareX Elsevier, 2016 21(2023), Seite 101291- (DE-627)824451805 (DE-600)2819369-6 23527110 nnns volume:21 year:2023 pages:101291- https://doi.org/10.1016/j.softx.2022.101291 kostenfrei https://doaj.org/article/bd32ca60bf7e4cb782b9d1a0ded18d80 kostenfrei http://www.sciencedirect.com/science/article/pii/S2352711022002096 kostenfrei https://doaj.org/toc/2352-7110 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 21 2023 101291-
spelling	10.1016/j.softx.2022.101291 doi (DE-627)DOAJ080553591 (DE-599)DOAJbd32ca60bf7e4cb782b9d1a0ded18d80 DE-627 ger DE-627 rakwb eng QA76.75-76.765 Binbin Lu verfasserin aut GWmodelS: A software for geographically weighted models 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Spatial heterogeneity or non-stationarity has become a popular and necessary concern in exploring relationships between variables. In this regard, geographically weighted (GW) models provide a powerful collection of techniques in its quantitative description. We developed a user-friendly, high-performance and systematic software, named GWmodelS, to promote better and broader usages of such models. Apart from a variety of GW models, including GW descriptive statistics, GW regression models, and GW principal components analysis, data management and mapping tools have also been incorporated with well-designed interfaces. Spatial heterogeneity Spatio-temporal models Visualization High-performance Local techniques Computer software Yigong Hu verfasserin aut Dongyang Yang verfasserin aut Yong Liu verfasserin aut Liuqi Liao verfasserin aut Zuoyao Yin verfasserin aut Tianyang Xia verfasserin aut Zheyi Dong verfasserin aut Paul Harris verfasserin aut Chris Brunsdon verfasserin aut Lex Comber verfasserin aut Guanpeng Dong verfasserin aut In SoftwareX Elsevier, 2016 21(2023), Seite 101291- (DE-627)824451805 (DE-600)2819369-6 23527110 nnns volume:21 year:2023 pages:101291- https://doi.org/10.1016/j.softx.2022.101291 kostenfrei https://doaj.org/article/bd32ca60bf7e4cb782b9d1a0ded18d80 kostenfrei http://www.sciencedirect.com/science/article/pii/S2352711022002096 kostenfrei https://doaj.org/toc/2352-7110 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 21 2023 101291-
allfields_unstemmed	10.1016/j.softx.2022.101291 doi (DE-627)DOAJ080553591 (DE-599)DOAJbd32ca60bf7e4cb782b9d1a0ded18d80 DE-627 ger DE-627 rakwb eng QA76.75-76.765 Binbin Lu verfasserin aut GWmodelS: A software for geographically weighted models 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Spatial heterogeneity or non-stationarity has become a popular and necessary concern in exploring relationships between variables. In this regard, geographically weighted (GW) models provide a powerful collection of techniques in its quantitative description. We developed a user-friendly, high-performance and systematic software, named GWmodelS, to promote better and broader usages of such models. Apart from a variety of GW models, including GW descriptive statistics, GW regression models, and GW principal components analysis, data management and mapping tools have also been incorporated with well-designed interfaces. Spatial heterogeneity Spatio-temporal models Visualization High-performance Local techniques Computer software Yigong Hu verfasserin aut Dongyang Yang verfasserin aut Yong Liu verfasserin aut Liuqi Liao verfasserin aut Zuoyao Yin verfasserin aut Tianyang Xia verfasserin aut Zheyi Dong verfasserin aut Paul Harris verfasserin aut Chris Brunsdon verfasserin aut Lex Comber verfasserin aut Guanpeng Dong verfasserin aut In SoftwareX Elsevier, 2016 21(2023), Seite 101291- (DE-627)824451805 (DE-600)2819369-6 23527110 nnns volume:21 year:2023 pages:101291- https://doi.org/10.1016/j.softx.2022.101291 kostenfrei https://doaj.org/article/bd32ca60bf7e4cb782b9d1a0ded18d80 kostenfrei http://www.sciencedirect.com/science/article/pii/S2352711022002096 kostenfrei https://doaj.org/toc/2352-7110 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 21 2023 101291-
allfieldsGer	10.1016/j.softx.2022.101291 doi (DE-627)DOAJ080553591 (DE-599)DOAJbd32ca60bf7e4cb782b9d1a0ded18d80 DE-627 ger DE-627 rakwb eng QA76.75-76.765 Binbin Lu verfasserin aut GWmodelS: A software for geographically weighted models 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Spatial heterogeneity or non-stationarity has become a popular and necessary concern in exploring relationships between variables. In this regard, geographically weighted (GW) models provide a powerful collection of techniques in its quantitative description. We developed a user-friendly, high-performance and systematic software, named GWmodelS, to promote better and broader usages of such models. Apart from a variety of GW models, including GW descriptive statistics, GW regression models, and GW principal components analysis, data management and mapping tools have also been incorporated with well-designed interfaces. Spatial heterogeneity Spatio-temporal models Visualization High-performance Local techniques Computer software Yigong Hu verfasserin aut Dongyang Yang verfasserin aut Yong Liu verfasserin aut Liuqi Liao verfasserin aut Zuoyao Yin verfasserin aut Tianyang Xia verfasserin aut Zheyi Dong verfasserin aut Paul Harris verfasserin aut Chris Brunsdon verfasserin aut Lex Comber verfasserin aut Guanpeng Dong verfasserin aut In SoftwareX Elsevier, 2016 21(2023), Seite 101291- (DE-627)824451805 (DE-600)2819369-6 23527110 nnns volume:21 year:2023 pages:101291- https://doi.org/10.1016/j.softx.2022.101291 kostenfrei https://doaj.org/article/bd32ca60bf7e4cb782b9d1a0ded18d80 kostenfrei http://www.sciencedirect.com/science/article/pii/S2352711022002096 kostenfrei https://doaj.org/toc/2352-7110 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 21 2023 101291-
allfieldsSound	10.1016/j.softx.2022.101291 doi (DE-627)DOAJ080553591 (DE-599)DOAJbd32ca60bf7e4cb782b9d1a0ded18d80 DE-627 ger DE-627 rakwb eng QA76.75-76.765 Binbin Lu verfasserin aut GWmodelS: A software for geographically weighted models 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Spatial heterogeneity or non-stationarity has become a popular and necessary concern in exploring relationships between variables. In this regard, geographically weighted (GW) models provide a powerful collection of techniques in its quantitative description. We developed a user-friendly, high-performance and systematic software, named GWmodelS, to promote better and broader usages of such models. Apart from a variety of GW models, including GW descriptive statistics, GW regression models, and GW principal components analysis, data management and mapping tools have also been incorporated with well-designed interfaces. Spatial heterogeneity Spatio-temporal models Visualization High-performance Local techniques Computer software Yigong Hu verfasserin aut Dongyang Yang verfasserin aut Yong Liu verfasserin aut Liuqi Liao verfasserin aut Zuoyao Yin verfasserin aut Tianyang Xia verfasserin aut Zheyi Dong verfasserin aut Paul Harris verfasserin aut Chris Brunsdon verfasserin aut Lex Comber verfasserin aut Guanpeng Dong verfasserin aut In SoftwareX Elsevier, 2016 21(2023), Seite 101291- (DE-627)824451805 (DE-600)2819369-6 23527110 nnns volume:21 year:2023 pages:101291- https://doi.org/10.1016/j.softx.2022.101291 kostenfrei https://doaj.org/article/bd32ca60bf7e4cb782b9d1a0ded18d80 kostenfrei http://www.sciencedirect.com/science/article/pii/S2352711022002096 kostenfrei https://doaj.org/toc/2352-7110 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 21 2023 101291-
language	English
source	In SoftwareX 21(2023), Seite 101291- volume:21 year:2023 pages:101291-
sourceStr	In SoftwareX 21(2023), Seite 101291- volume:21 year:2023 pages:101291-
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Spatial heterogeneity Spatio-temporal models Visualization High-performance Local techniques Computer software
isfreeaccess_bool	true
container_title	SoftwareX
authorswithroles_txt_mv	Binbin Lu @@aut@@ Yigong Hu @@aut@@ Dongyang Yang @@aut@@ Yong Liu @@aut@@ Liuqi Liao @@aut@@ Zuoyao Yin @@aut@@ Tianyang Xia @@aut@@ Zheyi Dong @@aut@@ Paul Harris @@aut@@ Chris Brunsdon @@aut@@ Lex Comber @@aut@@ Guanpeng Dong @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	824451805
id	DOAJ080553591
language_de	englisch
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callnumber-first	Q - Science
author	Binbin Lu
spellingShingle	Binbin Lu misc QA76.75-76.765 misc Spatial heterogeneity misc Spatio-temporal models misc Visualization misc High-performance misc Local techniques misc Computer software GWmodelS: A software for geographically weighted models
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topic_title	QA76.75-76.765 GWmodelS: A software for geographically weighted models Spatial heterogeneity Spatio-temporal models Visualization High-performance Local techniques
topic	misc QA76.75-76.765 misc Spatial heterogeneity misc Spatio-temporal models misc Visualization misc High-performance misc Local techniques misc Computer software
topic_unstemmed	misc QA76.75-76.765 misc Spatial heterogeneity misc Spatio-temporal models misc Visualization misc High-performance misc Local techniques misc Computer software
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title	GWmodelS: A software for geographically weighted models
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title_full	GWmodelS: A software for geographically weighted models
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title_sort	gwmodels: a software for geographically weighted models
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title_auth	GWmodelS: A software for geographically weighted models
abstract	Spatial heterogeneity or non-stationarity has become a popular and necessary concern in exploring relationships between variables. In this regard, geographically weighted (GW) models provide a powerful collection of techniques in its quantitative description. We developed a user-friendly, high-performance and systematic software, named GWmodelS, to promote better and broader usages of such models. Apart from a variety of GW models, including GW descriptive statistics, GW regression models, and GW principal components analysis, data management and mapping tools have also been incorporated with well-designed interfaces.
abstractGer	Spatial heterogeneity or non-stationarity has become a popular and necessary concern in exploring relationships between variables. In this regard, geographically weighted (GW) models provide a powerful collection of techniques in its quantitative description. We developed a user-friendly, high-performance and systematic software, named GWmodelS, to promote better and broader usages of such models. Apart from a variety of GW models, including GW descriptive statistics, GW regression models, and GW principal components analysis, data management and mapping tools have also been incorporated with well-designed interfaces.
abstract_unstemmed	Spatial heterogeneity or non-stationarity has become a popular and necessary concern in exploring relationships between variables. In this regard, geographically weighted (GW) models provide a powerful collection of techniques in its quantitative description. We developed a user-friendly, high-performance and systematic software, named GWmodelS, to promote better and broader usages of such models. Apart from a variety of GW models, including GW descriptive statistics, GW regression models, and GW principal components analysis, data management and mapping tools have also been incorporated with well-designed interfaces.
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title_short	GWmodelS: A software for geographically weighted models
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GWmodelS: A software for geographically weighted models

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