# densityfun.ppp

##### 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.

##### 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`

.

##### See Also

To interpolate values observed at the points, use `Smoothfun`

.

##### Examples

```
# NOT RUN {
f <- densityfun(swedishpines)
f
f(42, 60)
plot(f)
# }
```

*Documentation reproduced from package spatstat, version 1.63-0, License: GPL (>= 2)*