GWR Gaussian weights function

The gwr.gauss function returns a vector of weights using the Gaussian scheme:

$$w(g) = e^{{-(d/h)}^2}$$

where \(d\) are the distances between the observations and \(h\) is the bandwidth.

The default (from release 0.5) gwr.Gauss function returns a vector of weights using the Gaussian scheme:

$$w(g) = e^{-(1/2) {{(d/h)}^2}}$$

gwr.gauss(dist2, bandwidth)
gwr.Gauss(dist2, bandwidth)

Arguments

dist2

vector of squared distances between observations and fit point

bandwidth

bandwidth

Value

vector of weights.

References

Fotheringham, A.S., Brunsdon, C., and Charlton, M.E., 2000, Quantitative Geography, London: Sage; C. Brunsdon, A.Stewart Fotheringham and M.E. Charlton, 1996, "Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity", Geographical Analysis, 28(4), 281-298; http://gwr.nuim.ie/

Author

Roger Bivand Roger.Bivand@nhh.no

See also

gwr.sel, gwr

Examples

plot(seq(-10,10,0.1), gwr.Gauss(seq(-10,10,0.1)^2, 3.5), type="l")