A - Papers appearing in refereed journals
Lu, B., Hu, Y., Yang, D., Liu, Y., Liao, L., Yin, Z., Xia, T., Dong, Z., Harris, P., Brunsdon, C., Comber, A. and Dong, G. 2023. GWmodelS A software for geographically weighted models. SoftwareX. 21, p. 101291. https://doi.org/10.1016/j.softx.2022.101291
Authors | Lu, B., Hu, Y., Yang, D., Liu, Y., Liao, L., Yin, Z., Xia, T., Dong, Z., Harris, P., Brunsdon, C., Comber, A. and Dong, G. |
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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. |
Keywords | Spatial heterogeneity; Spatio-temporal models; Visualization; High-performance; Local techniques |
Year of Publication | 2023 |
Journal | SoftwareX |
Journal citation | 21, p. 101291 |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.softx.2022.101291 |
Open access | Published as ‘gold’ (paid) open access |
Funder | National Natural Science Foundation of China |
Publisher's version | |
Output status | Published |
Publication dates | |
Online | 16 Dec 2022 |
Publication process dates | |
Accepted | 07 Dec 2022 |
Publisher | Elsevier |
ISSN | 2352-7110 |
Permalink - https://repository.rothamsted.ac.uk/item/98v22/gwmodels-a-software-for-geographically-weighted-models