The function returns a vector of weights using
the bisquare scheme:

$$w_{ij}(g) = (1 - (d_{ij}^2/d^2))^2 $$
if \(d_{ij} <= d\) else \(w_{ij}(g) = 0\), where \(d_{ij}\)
are the distances between the observations
and \(d\) is the distance at which weights are set to zero.

gwr.bisquare(dist2, d)

## Arguments

dist2 |
vector of squared distances between observations |

d |
distance at which weights are set to zero |

## Value

matrix 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/

## See also

## Examples