gwr.vdp: Collinearity diagnostics for geographically weighted...

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/gwr.vdp.R

Description

Uses the collinearity diagnostic tools of variance-decomposition proportions and condition indexes for geographically weighted regression (GWR) models.

Usage

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gwr.vdp(form, locs, data, phi, kernel = "exp", sel.ci = 30, sel.vdp = 0.5)

Arguments

form

A regression model forumula, as in the functions lm and glm

locs

A matrix of spatial coordinates of data points, where the x coordinate is first, then the y coordinate; coordinates are assumed to not be latitude and longitude, as Euclidean distance is calculated from coordinates

data

A data frame with data to fit model

phi

The kernel bandwidth used in the GWR model

kernel

The kernel weighting function used in the GWR model, either exp or gauss; exp is the default

sel.ci

The threshold value to use for the condition index to indicate observations with a collinearity issue; indexes above this value will be flagged; the default is 30

sel.vdp

The threshold value to use for the variance-decomposition proportion to indicate observations with a collinearity issue; proportions above this value will be flagged; the default is 0.5

Details

This function calculates the variance-decomposition proportions and the condition indexes for the weighted design matrix used in a GWR model. The kernel function and bandwidth used to estimate the GWR model must be input to this function. Observations with a large condition index and relatively large variance-decomposition proportions for more than one regression term indicate an issue with collinearity.

Value

A list with the following items:

condition

Largest condition index for each observation

vdp

Variance-decomposition proportions for the largest variance component for each observation

flag.cond

True if largest condition index exceeds threshold

flag.vdp

True if variance-decomposition proportions for more than one term exceed threshold

flag.cond.vdp

True if condition index and variance-decompostion proportions exceed thresholds

Author(s)

David Wheeler

References

Wheeler DC (2007) Diagnostic tools and a remedial method for collinearity in geographically weighted regression. Environment and Planning A, 39: 2464-2481

See Also

gwr.bw.est

Examples

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data(columbus)
locs <- cbind(columbus$x, columbus$y)
col.bw <- gwr.bw.est(crime ~ income + houseval, locs, columbus, "exp")
col.vdp <- gwr.vdp(crime ~ income + houseval, locs, columbus, col.bw$phi, "exp")
hist(col.vdp$condition)

Example output

Loading required package: fields
Loading required package: spam
Loading required package: dotCall64
Loading required package: grid
Spam version 2.2-2 (2019-03-07) is loaded.
Type 'help( Spam)' or 'demo( spam)' for a short introduction 
and overview of this package.
Help for individual functions is also obtained by adding the
suffix '.spam' to the function name, e.g. 'help( chol.spam)'.

Attaching package: 'spam'

The following objects are masked from 'package:base':

    backsolve, forwardsolve

Loading required package: maps
See https://github.com/NCAR/Fields for
 an extensive vignette, other supplements and source code 
Loading required package: lars
Loaded lars 1.2

[1] "Bandwidth:  21.07  RMSPE : 12.21"
[1] "Bandwidth:  15.87  RMSPE : 12.16"
[1] "Bandwidth:  11.97  RMSPE : 12.1"
[1] "Bandwidth:  9.051  RMSPE : 12.02"
[1] "Bandwidth:  6.858  RMSPE : 11.94"
[1] "Bandwidth:  5.214  RMSPE : 11.86"
[1] "Bandwidth:  3.98  RMSPE : 11.81"
[1] "Bandwidth:  3.055  RMSPE : 11.74"
[1] "Bandwidth:  2.361  RMSPE : 11.59"
[1] "Bandwidth:  0.8003  RMSPE : 11.68"
[1] "Bandwidth:  1.971  RMSPE : 11.41"
[1] "Bandwidth:  1.678  RMSPE : 11.24"
[1] "Bandwidth:  1.02  RMSPE : 11.19"
[1] "Bandwidth:  1.514  RMSPE : 11.14"
[1] "Bandwidth:  1.267  RMSPE : 11.07"

gwrr documentation built on May 2, 2019, 7:07 a.m.