# density.ppp

0th

Percentile

##### Kernel Smoothed Intensity of Point Pattern

Compute a kernel smoothed intensity function from a point pattern.

Keywords
methods, smooth, spatial
##### Usage
## S3 method for class 'ppp':
density(x, sigma, \dots, 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.
##### 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.

##### Value

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

##### synopsis

## S3 method for class 'ppp': density(x, sigma, \dots, edge=TRUE)

ppp.object, im.object

• density.ppp
##### Examples
data(cells)
Z <- density.ppp(cells, 0.05)
plot(Z)
Documentation reproduced from package spatstat, version 1.9-3, License: GPL version 2 or newer

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