Wayne Jones <wayne.w.jones@shell.com>, Ludger Evers
<ludger.evers@glasgow.ac.uk>, Andrej Aderhold
<andrej.aderhold@protonmail.com>
Shiny application for the analysis of groundwater
monitoring data, designed to work with simple time-series data for
solute concentration and ground water elevation, but can also plot
non-aqueous phase liquid (NAPL) thickness if required. Also provides
the import of a site basemap in GIS shapefile format.
deldir, digest, geometry, Kendall, lattice, MASS, Matrix,
officer, raster, readxl, rhandsontable, sf, shiny,
shinycssloaders, shinydashboard, shinyjs, sm, sp, splancs, zoo

deldir, digest, geometry, Kendall, lattice, lubridate, MASS,
Matrix, officer, raster, readxl, rhandsontable, sf, shiny,
shinycssloaders, shinydashboard, shinyjs, sm, sp, splancs, zoo

deldir, digest, geometry, Kendall, lattice, lubridate, MASS,
Matrix, officer (>= 0.3.8), raster, readxl, rhandsontable, sf,
shiny, shinycssloaders, shinydashboard, shinyjs, sm, sp,
splancs, zoo

Binbin Lu, Paul Harris, Isabella Gollini, Martin Charlton,
Chris Brunsdon
Functions for computing geographically weighted models
We gratefully acknowledge support from Science Foundation
Ireland under the National Development Plan through the award
of a Strategic Research Centre grant 07-SRC-I1168

Binbin Lu, Paul Harris, Isabella Gollini, Martin Charlton, Chris Brunsdon
Functions for computing geographically weighted
models

Binbin Lu, Paul Harris, Martin Charlton, Chris Brunsdon, Tomoki Nakaya, Isabella Gollini

Binbin Lu[aut], Paul Harris[aut], Martin Charlton[aut], Chris Brunsdon[aut], Tomoki Nakaya[aut], Isabella Gollini[ctb]

R (>= 3.0.0),maptools (>= 0.5-2), robustbase,sp
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.