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