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 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/