# Geographically-Weighted Models

## Documentation for package ‘GWmodel’ version 2.4-1

- DESCRIPTION file.

## Help Pages

A B C D E F G L M N P R S T U W

GWmodel-package | Geographically-Weighted Models

## -- A --

AICc | Model selection for GWR with a given set of independent variables
AICc1 | Scalable GWR
AICc_rss | Model selection for GWR with a given set of independent variables
AICc_rss1 | Bandwidth selection for basic GWR

## -- B --

bias.bs | Bootstrap GWR
bw.ggwr | Bandwidth selection for generalised geographically weighted regression (GWR)
bw.gtwr | Bandwidth selection for GTWR
bw.gwda | Bandwidth selection for GW Discriminant Analysis
bw.gwpca | Bandwidth selection for Geographically Weighted Principal Components Analysis (GWPCA)
bw.gwr | Bandwidth selection for basic GWR
bw.gwr.lcr | Bandwidth selection for locally compensated ridge GWR (GWR-LCR)
bw.gwr1 | Minkovski approach for GWR
bw.gwr3 | Bootstrap GWR
bw.gwss.average | Bandwidth selection for GW summary averages

## -- C --

check.components | Interaction tool with the GWPCA glyph map
ci.bs | Bootstrap GWR
Ci_mat | Basic GWR model
confusion.matrix | GW Discriminant Analysis

## -- D --

Dub.voter | Voter turnout data in Greater Dublin(SpatialPolygonsDataFrame)
DubVoter | Voter turnout data in Greater Dublin(SpatialPolygonsDataFrame)

## -- E --

ehat | Model selection for GWR with a given set of independent variables
EWHP | House price data set (DataFrame) in England and Wales
ewhp | House price data set (DataFrame) in England and Wales
ewoutline | Outline of England and Wales for data EWHP
extract.mat | Model selection for GWR with a given set of independent variables
e_vec | Bandwidth selection for basic GWR

## -- F --

F1234.test | Basic GWR model
fitted | Bandwidth selection for basic GWR

## -- G --

Gedu.counties | Georgia counties data (SpatialPolygonsDataFrame)
Gedu.df | Georgia census data set (csv file)
Generate.formula | Model selection for GWR with a given set of independent variables
generate.lm.data | Bootstrap GWR
Georgia | Georgia census data set (csv file)
ggwr.aic | Bandwidth selection for generalised geographically weighted regression (GWR)
ggwr.basic | Generalised GWR models with Poisson and Binomial options
ggwr.cv | Cross-validation score for a specified bandwidth for generalised GWR
ggwr.cv.contrib | Cross-validation data at each observation location for a generalised GWR model
glyph.plot | Multivariate glyph plots of GWPCA loadings
gold | Bandwidth selection for basic GWR
grouping.xy | GW Discriminant Analysis
gtwr | Geographically and Temporally Weighted Regression
gtwr.aic | Bandwidth selection for GTWR
gtwr.cv | Bandwidth selection for GTWR
gw.average.cv | Bandwidth selection for GW summary averages
gw.average.cv.contrib | Bandwidth selection for GW summary averages
gw.dist | Distance matrix calculation
gw.fitted | Model selection for GWR with a given set of independent variables
gw.mean.cv | Bandwidth selection for GW summary averages
gw.median.cv | Bandwidth selection for GW summary averages
gw.pcplot | Geographically weighted parallel coordinate plot for investigating multivariate data sets
gw.reg1 | GWR used as a spatial predictor
gw.weight | Weight matrix calculation
gwda | GW Discriminant Analysis
GWmodel | Geographically-Weighted Models
gwpca | GWPCA
gwpca.check.components | Interaction tool with the GWPCA glyph map
gwpca.cv | Cross-validation score for a specified bandwidth for GWPCA
gwpca.cv.contrib | Cross-validation data at each observation location for a GWPCA
gwpca.glyph.plot | Multivariate glyph plots of GWPCA loadings
gwpca.montecarlo.1 | Monte Carlo (randomisation) test for significance of GWPCA eigenvalue variability for the first component only - option 1
gwpca.montecarlo.2 | Monte Carlo (randomisation) test for significance of GWPCA eigenvalue variability for the first component only - option 2
gwr.aic | Bandwidth selection for basic GWR
gwr.aic1 | Minkovski approach for GWR
gwr.backfit | Multiscale GWR
gwr.basic | Basic GWR model
gwr.binomial | Generalised GWR models with Poisson and Binomial options
gwr.binomial.wt | Generalised GWR models with Poisson and Binomial options
gwr.bootstrap | Bootstrap GWR
gwr.collin.diagno | Local collinearity diagnostics for basic GWR
gwr.cv | Cross-validation score for a specified bandwidth for basic GWR
gwr.cv.contrib | Cross-validation data at each observation location for a basic GWR model
gwr.cv1 | Minkovski approach for GWR
gwr.fitted | Generalised GWR models with Poisson and Binomial options
gwr.generalised | Generalised GWR models with Poisson and Binomial options
gwr.hetero | Heteroskedastic GWR
gwr.lcr | GWR with a locally-compensated ridge term
gwr.lcr.cv | Cross-validation score for a specified bandwidth for GWR-LCR model
gwr.lcr.cv.contrib | Cross-validation data at each observation location for the GWR-LCR model
gwr.mink.approach | Minkovski approach for GWR
gwr.mink.matrixview | Visualisation of the results from 'gwr.mink.approach'
gwr.mink.pval | Select the values of p for the Minkowski approach for GWR
gwr.mink.pval.backward | Select the values of p for the Minkowski approach for GWR
gwr.mink.pval.forward | Select the values of p for the Minkowski approach for GWR
gwr.mixed | Mixed GWR
gwr.mixed.2 | Mixed GWR
gwr.mixed.2.fast | Mixed GWR
gwr.mixed.trace | Mixed GWR
gwr.mixed.trace.fast | Mixed GWR
gwr.model.selection | Model selection for GWR with a given set of independent variables
gwr.model.sort | Sort the results of the GWR model selection function 'gwr.model.selection'.
gwr.model.view | Visualise the GWR models from 'gwr.model.selection'
gwr.montecarlo | Monte Carlo (randomisation) test for significance of GWR parameter variability
gwr.multiscale | Multiscale GWR
gwr.poisson | Generalised GWR models with Poisson and Binomial options
gwr.poisson.wt | Generalised GWR models with Poisson and Binomial options
gwr.predict | GWR used as a spatial predictor
gwr.q | Mixed GWR
gwr.q2 | Multiscale GWR
gwr.robust | Robust GWR model
gwr.scalable | Scalable GWR
gwr.scalable.loocv | Scalable GWR
gwr.t.adjust | Adjust p-values for multiple hypothesis tests in basic GWR
gwr.write | Write the GWR results into files
gwr.write.shp | Write the GWR results into files
gwrt.err | Bootstrap GWR
gwrt.lag | Bootstrap GWR
gwrt.mlr | Bootstrap GWR
gwrt.sma | Bootstrap GWR
gwrtvar | Bootstrap GWR
gwr_diag | Basic GWR model
gwr_diag1 | Scalable GWR
gwr_mixed_2 | Mixed GWR
gwr_mixed_trace | Mixed GWR
gwr_q | Mixed GWR
gwss | Geographically weighted summary statistics (GWSS)
gwss.montecarlo | Monte Carlo (randomisation) test for gwss
gw_BIC | Bandwidth selection for basic GWR
gw_cv_all | Bandwidth selection for basic GWR
gw_cv_all_cuda | Bandwidth selection for basic GWR
gw_cv_all_omp | Basic GWR model
gw_dist | Distance matrix calculation
gw_fitted | Multiscale GWR
gw_local_r2 | Basic GWR model
gw_reg | Basic GWR model
gw_reg_1 | Basic GWR model
gw_reg_2 | Basic GWR model
gw_reg_all | Basic GWR model
gw_reg_all_cuda | Basic GWR model
gw_reg_all_omp | Basic GWR model
gw_weight | Weight matrix calculation
gw_weight_mat | Weight matrix calculation
gw_weight_vec | Weight matrix calculation

## -- L --

local.corr | Geographically weighted summary statistics (GWSS)
LondonBorough | London boroughs data
londonborough | London boroughs data
LondonHP | London house price data set (SpatialPointsDataFrame)
londonhp | London house price data set (SpatialPointsDataFrame)

## -- M --

mink.approach | Minkovski approach for GWR
mink.matrixview | Visualisation of the results from 'gwr.mink.approach'
model.selection.gwr | Model selection for GWR with a given set of independent variables
model.sort.gwr | Sort the results of the GWR model selection function 'gwr.model.selection'.
model.view.gwr | Visualise the GWR models from 'gwr.model.selection'
montecarlo.gwpca.1 | Monte Carlo (randomisation) test for significance of GWPCA eigenvalue variability for the first component only - option 1
montecarlo.gwpca.2 | Monte Carlo (randomisation) test for significance of GWPCA eigenvalue variability for the first component only - option 2
montecarlo.gwr | Monte Carlo (randomisation) test for significance of GWR parameter variability
montecarlo.gwss | Monte Carlo (randomisation) test for gwss

## -- N --

new_multiscale | Multiscale GWR

## -- P --

parametric.bs | Bootstrap GWR
parametric.bs.local | Bootstrap GWR
plot.mcsims | Monte Carlo (randomisation) test for significance of GWPCA eigenvalue variability for the first component only - option 1
plot.pvlas | Select the values of p for the Minkowski approach for GWR
print.ggwrm | Generalised GWR models with Poisson and Binomial options
print.gtwrm | Geographically and Temporally Weighted Regression
print.gwda | GW Discriminant Analysis
print.gwpca | GWPCA
print.gwrbsm | Bootstrap GWR
print.gwrlcr | GWR with a locally-compensated ridge term
print.gwrm | Basic GWR model
print.gwrm.pred | GWR used as a spatial predictor
print.gwss | Geographically weighted summary statistics (GWSS)
print.mgwr | Mixed GWR
print.multiscalegwr | Multiscale GWR
print.scgwrm | Scalable GWR
pval.bs | Bootstrap GWR

## -- R --

ridge.lm | GWR with a locally-compensated ridge term
robustSvd | GWPCA
rss | Model selection for GWR with a given set of independent variables
rwpca | GWPCA

## -- S --

scgwr_loocv | Scalable GWR
scgwr_pre | Scalable GWR
scgwr_reg | Scalable GWR
se.bs | Bootstrap GWR
splitx | GW Discriminant Analysis
st.dist | Spatio-temporal distance matrix calculation

## -- T --

ti.dist | Geographically and Temporally Weighted Regression
ti.distm | Geographically and Temporally Weighted Regression
ti.distv | Geographically and Temporally Weighted Regression
trhat2 | Basic GWR model

## -- U --

USelect2004 | Results of the 2004 US presidential election at the county level (SpatialPolygonsDataFrame)

## -- W --

wlda | GW Discriminant Analysis
wlda.cr | Bandwidth selection for GW Discriminant Analysis
wmean | GW Discriminant Analysis
wpca | GWPCA
wprior | GW Discriminant Analysis
wqda | GW Discriminant Analysis
wqda.cr | Bandwidth selection for GW Discriminant Analysis
writeGWR | Write the GWR results into files
writeGWR.shp | Write the GWR results into files
wt.median | GWPCA
wvarcov | GW Discriminant Analysis