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GWmodel (version 2.2-4)

Geographically-Weighted Models

Description

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 (Brunsdon et al., 2002), GW principal components analysis (Harris et al., 2011), GW discriminant analysis (Brunsdon et al., 2007) and various forms of GW regression (Brunsdon et al., 1996); some of which are provided in basic and robust (outlier resistant) forms.

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Version

Install

install.packages('GWmodel')

Monthly Downloads

1,644

Version

2.2-4

License

GPL (>= 2)

Maintainer

Binbin Lu

Last Published

February 17th, 2021

Functions in GWmodel (2.2-4)

USelect

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

House price data set (DataFrame) in England and Wales
EWOutline

GWmodel-package

Geographically-Weighted Models
ggwr.basic

Generalised GWR models with Poisson and Binomial options
ggwr.cv

Cross-validation score for a specified bandwidth for generalised GWR
gw.weight

Weight matrix calculation
gwpca.glyph.plot

Multivariate glyph plots of GWPCA loadings
gwda

GW Discriminant Analysis
gwpca.montecarlo.2

Monte Carlo (randomisation) test for significance of GWPCA eigenvalue variability for the first component only - option 2
ggwr.cv.contrib

Cross-validation data at each observation location for a generalised GWR model
gwpca.montecarlo.1

Monte Carlo (randomisation) test for significance of GWPCA eigenvalue variability for the first component only - option 1
gwr.basic

Basic GWR model
gwr.lcr.cv.contrib

Cross-validation data at each observation location for the GWR-LCR model
bw.gtwr

Bandwidth selection for GTWR
gwr.lcr.cv

Cross-validation score for a specified bandwidth for GWR-LCR model
gwr.multiscale

Multiscale GWR
bw.gwpca

Bandwidth selection for Geographically Weighted Principal Components Analysis (GWPCA)
bw.gwda

Bandwidth selection for GW Discriminant Analysis
gtwr

Geographically and Temporally Weighted Regression
gwpca.cv.contrib

Cross-validation data at each observation location for a GWPCA
gwpca.cv

Cross-validation score for a specified bandwidth for GWPCA
gwr.predict

GWR used as a spatial predictor
gwr.hetero

Heteroskedastic GWR
gw.dist

Distance matrix calculation
bw.gwr

Bandwidth selection for basic GWR
gw.pcplot

Geographically weighted parallel coordinate plot for investigating multivariate data sets
gwr.lcr

GWR with a locally-compensated ridge term
gwr.cv.contrib

Cross-validation data at each observation location for a basic GWR model
gwr.model.selection

Model selection for GWR with a given set of independent variables
gwr.cv

Cross-validation score for a specified bandwidth for basic GWR
gwr.bootstrap

Bootstrap GWR
gwr.model.sort

LondonHP

London house price data set (SpatialPointsDataFrame)
LondonBorough

London boroughs data
gwr.mink.pval

Select the values of p for the Minkowski approach for GWR
bw.gwr.lcr

Bandwidth selection for locally compensated ridge GWR (GWR-LCR)
bw.gwss.average

Bandwidth selection for GW summary averages
gwpca.check.components

Interaction tool with the GWPCA glyph map
gwpca

GWPCA
gwr.mixed

Mixed GWR
gwr.scalable

Scalable GWR
gwr.robust

Robust GWR model
gwss

Geographically weighted summary statistics (GWSS)
gwr.model.view

gwr.collin.diagno

Local collinearity diagnostics for basic GWR
gwr.mink.matrixview

gwr.write

Write the GWR results into files
gwr.t.adjust

Adjust p-values for multiple hypothesis tests in basic GWR
gwr.mink.approach

Minkovski approach for GWR
gwr.montecarlo

Monte Carlo (randomisation) test for significance of GWR parameter variability
gwss.montecarlo

Georgia

Georgia census data set (csv file)
GeorgiaCounties

Georgia counties data (SpatialPolygonsDataFrame)
DubVoter

Voter turnout data in Greater Dublin(SpatialPolygonsDataFrame)
bw.ggwr

Bandwidth selection for generalised geographically weighted regression (GWR)