GWR Gaussian weights function
gwr.gauss.RdThe 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/
