View source: R/adaptive.density.R
adaptive.density | R Documentation |
Computes an adaptive estimate of the intensity function of a point pattern.
adaptive.density(X, ..., method=c("voronoi","kernel", "nearest"))
X |
Point pattern (object of class |
method |
Character string specifying the estimation method |
... |
Additional arguments passed to
|
This function is an alternative to density.ppp
and density.lpp
. It
computes an estimate of the intensity function of a point pattern
dataset. The result is a pixel image giving the estimated intensity.
If method="voronoi"
the data are passed to the function
densityVoronoi
which estimates the intensity using
the Voronoi-Dirichlet tessellation.
If method="kernel"
the data are passed to the function
densityAdaptiveKernel.ppp
which estimates the intensity
using a variable-bandwidth kernel estimator. (This is not yet supported
when X
has class "lpp"
.)
If method="nearest"
the data are passed to the function
nndensity.ppp
which estimates the intensity using the
distance to the k
-th nearest data point. (This is not yet supported
when X
has class "lpp"
.)
A pixel image (object of class "im"
or "linim"
)
whose values are estimates of the intensity of X
.
and \mehdi.
density.ppp
,
densityVoronoi
,
densityAdaptiveKernel.ppp
,
nndensity.ppp
,
im.object
.
plot(adaptive.density(nztrees, 1), main="Voronoi estimate")
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