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}}*

1 2 |

`dist2` |
vector of squared distances between observations and fit point |

`bandwidth` |
bandwidth |

vector of weights.

Roger Bivand Roger.Bivand@nhh.no

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/

`gwr.sel`

, `gwr`

1 |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.