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.stoyan
h <- bw.frac(letterR)
h
plot(h, main="bw.frac(letterR)")
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