bw.frac(X, ..., f=1/4)"owin") or
point pattern (object of class "ppp")
or other data which can be converted to a window
using as.owin.distcdf."bw.frac"
which can be plotted to show the cumulative distribution function
and the selected quantile.sigma
for the kernel estimator of point process intensity
computed by density.ppp.The bandwidth $\sigma$ is computed as a quantile of the distance between two independent random points in the window. The default is the lower quartile of this distribution.
If $F(r)$ is the cumulative distribution function of the distance between two independent random points uniformly distributed in the window, then the value returned is the quantile with probability $f$. That is, the bandwidth is the value $r$ such that $F(r) = f$.
The cumulative distribution function $F(r)$ is
computed using distcdf. We then
we compute the smallest number $r$
such that $F(r) \ge f$.
density.ppp,
bw.diggle,
bw.relrisk,
bw.scott,
bw.smoothppp,
bw.stoyanh <- bw.frac(letterR)
h
plot(h, main="bw.frac(letterR)")Run the code above in your browser using DataLab