# densityfun.ppp

0th

Percentile

##### Kernel Estimate of Intensity as a Spatial Function

Compute a kernel estimate of intensity for a point pattern, and return the result as a function of spatial location.

Keywords
methods, smooth, spatial
##### Usage
densityfun(X, …)# S3 method for ppp
densityfun(X, sigma = NULL, …,
weights = NULL, edge = TRUE, diggle = FALSE)
##### Arguments
X

Point pattern (object of class "ppp").

sigma

Smoothing bandwidth, or bandwidth selection function, passed to density.ppp.

Additional arguments passed to density.ppp.

weights

Optional vector of weights associated with the points of X.

edge,diggle

Logical arguments controlling the edge correction. Arguments passed to density.ppp.

##### Details

The commands densityfun and density both perform kernel estimation of the intensity of a point pattern. The difference is that density returns a pixel image, containing the estimated intensity values at a grid of locations, while densityfun returns a function(x,y) which can be used to compute the intensity estimate at any spatial location. For purposes such as model-fitting it is more accurate to use densityfun.

##### Value

A function with arguments x,y returning values of the intensity. The function also belongs to the class "densityfun" which has methods for print and as.im. It also belongs to the class "funxy" which has methods for plot, contour and persp.

density.

To interpolate values observed at the points, use Smoothfun.

##### Aliases
• densityfun
• densityfun.ppp
##### Examples
# NOT RUN {
f <- densityfun(swedishpines)
f
f(42, 60)
plot(f)
# }

Documentation reproduced from package spatstat, version 1.57-1, License: GPL (>= 2)

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