ksmooth.ppp: Kernel Smoothed Intensity of Point Pattern
Description
Compute a kernel smoothed intensity function from a point pattern.Usage
ksmooth.ppp(x, sigma, weights, edge=TRUE)
Arguments
x
Point pattern (object of class "ppp"
) to be smoothed.
sigma
Standard deviation of isotropic Gaussian smoothing kernel.
weights
Optional vector of weights to be attached to the points.
May include negative values.
edge
Logical flag: if TRUE
, apply edge correction.
Value
- A pixel image (object of class
"im"
).
synopsis
ksmooth.ppp(x, sigma, ..., edge=TRUE)Details
A kernel estimate of the intensity of the point pattern
is computed. The result is
the convolution of the isotropic Gaussian kernel with
standard deviation sigma
and point masses at each of the data
points. The default is to assign
a unit weight to each point.
If weights
is present, the point masses have these
weights (which may be signed real numbers). Computation is performed using the Fast Fourier Transform.
Examples
Run this codedata(cells)
Z <- ksmooth.ppp(cells, 0.05)
plot(Z)
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