spatstat (version 1.5-6)

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.

See Also

ppp.object, im.object

Examples

Run this code
data(cells)
  Z <- ksmooth.ppp(cells, 0.05)
  plot(Z)

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