density.ppp: Kernel Smoothed Intensity of Point Pattern
Description
Compute a kernel smoothed intensity function from a point pattern.Usage
density.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.
...
Arguments passed to as.mask
to determine
the pixel resolution. edge
Logical flag: if TRUE
, apply edge correction.
Value
- A pixel image (object of class
"im"
).
synopsis
density.ppp(x, sigma, ..., edge=TRUE)Details
This is a method for the generic function density
.
A kernel estimate of the intensity function of the point pattern
is computed. The result is
the convolution of the isotropic Gaussian kernel of
standard deviation sigma
with 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). If edge=TRUE
, the intensity estimate is corrected for
edge effect bias by dividing it by the convolution of the
Gaussian kernel with the window of observation.
Computation is performed using the Fast Fourier Transform.