ksmooth.ppp

0th

Percentile

Kernel Smoothed Intensity of Point Pattern

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.
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.

Value

  • A pixel image (object of class "im").

synopsis

ksmooth.ppp(x, sigma, ..., edge=TRUE)

See Also

ppp.object, im.object

Aliases
  • ksmooth.ppp
Examples
require(spatstat)
  data(cells)
  Z <- ksmooth.ppp(cells, 0.05)
  plot(Z)
Documentation reproduced from package spatstat, version 1.4-3, License: GPL version 2 or newer

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