GWmodel-package: Geographically-Weighted Models
In GWmodel: Geographically-Weighted Models
GWmodel-package R Documentation
Geographically-Weighted Models
Description
In GWmodel, we introduce techniques from a particular branch of spatial statistics,
termed geographically-weighted (GW) models. GW models suit situations when data are
not described well by some global model, but where there are spatial regions where
a suitably localised calibration provides a better description. GWmodel includes functions
to calibrate: GW summary statistics, GW principal components analysis, GW discriminant analysis
and various forms of GW regression; some of which are provided in basic and robust (outlier resistant) forms.
In particular, the high-performence computing technologies, including multi-thread and CUDA techniques are started
to be adopted for efficient calibrations.
Details
Package: GWmodel
Type: Package
Version: 2.3-1
Date: 2023-07-10
License: GPL (>=2)
LazyLoad: yes
Note
Acknowledgements: We gratefully acknowledge support from National Natural Science Foundation of China (42071368); Science Foundation Ireland
under the National Development Plan through the award of a Strategic Research Centre
grant 07-SRC-I1168.
Beta versions can always be found at https://github.com/lbb220/GWmodel,
which includes all the newly developed functions for GW models.
For latest tutorials on using GWmodel please go to: https://rpubs.com/gwmodel
Author(s)
Binbin Lu, Paul Harris, Martin Charlton, Chris Brunsdon, Tomoki Nakaya, Daisuke Murakami,Isabella Gollini[ctb], Yigong Hu[ctb], Fiona H Evans[ctb]
Maintainer: Binbin Lu <binbinlu@whu.edu.cn>
References
Gollini I, Lu B, Charlton M, Brunsdon C, Harris P (2015) GWmodel: an R Package
for exploring Spatial Heterogeneity using Geographically Weighted Models. Journal
of Statistical Software, 63(17):1-50, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v063.i17")}
Lu B, Harris P, Charlton M, Brunsdon C (2014) The GWmodel R Package: further
topics for exploring Spatial Heterogeneity using Geographically Weighted Models.
Geo-spatial Information Science 17(2): 85-101, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/10095020.2014.917453")}
GWmodel documentation built on July 9, 2023, 5:52 p.m.
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| GWmodel-package | R Documentation |
Geographically-Weighted Models
Description
In GWmodel, we introduce techniques from a particular branch of spatial statistics, termed geographically-weighted (GW) models. GW models suit situations when data are not described well by some global model, but where there are spatial regions where a suitably localised calibration provides a better description. GWmodel includes functions to calibrate: GW summary statistics, GW principal components analysis, GW discriminant analysis and various forms of GW regression; some of which are provided in basic and robust (outlier resistant) forms. In particular, the high-performence computing technologies, including multi-thread and CUDA techniques are started to be adopted for efficient calibrations.
Details
| Package: | GWmodel |
| Type: | Package |
| Version: | 2.3-1 |
| Date: | 2023-07-10 |
| License: | GPL (>=2) |
| LazyLoad: | yes |
Note
Acknowledgements: We gratefully acknowledge support from National Natural Science Foundation of China (42071368); Science Foundation Ireland under the National Development Plan through the award of a Strategic Research Centre grant 07-SRC-I1168.
Beta versions can always be found at https://github.com/lbb220/GWmodel, which includes all the newly developed functions for GW models.
For latest tutorials on using GWmodel please go to: https://rpubs.com/gwmodel
Author(s)
Binbin Lu, Paul Harris, Martin Charlton, Chris Brunsdon, Tomoki Nakaya, Daisuke Murakami,Isabella Gollini[ctb], Yigong Hu[ctb], Fiona H Evans[ctb]
Maintainer: Binbin Lu <binbinlu@whu.edu.cn>
References
Gollini I, Lu B, Charlton M, Brunsdon C, Harris P (2015) GWmodel: an R Package for exploring Spatial Heterogeneity using Geographically Weighted Models. Journal of Statistical Software, 63(17):1-50, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v063.i17")}
Lu B, Harris P, Charlton M, Brunsdon C (2014) The GWmodel R Package: further topics for exploring Spatial Heterogeneity using Geographically Weighted Models. Geo-spatial Information Science 17(2): 85-101, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/10095020.2014.917453")}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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