# density.splitppp: Kernel Smoothed Intensity of Split Point Pattern In spatstat: Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests

## Description

Compute a kernel smoothed intensity function for each of the components of a split point pattern, or each of the point patterns in a list.

## Usage

 ```1 2 3 4 5``` ``` ## S3 method for class 'splitppp' density(x, ..., se=FALSE) ## S3 method for class 'ppplist' density(x, ..., se=FALSE) ```

## Arguments

 `x` Split point pattern (object of class `"splitppp"` created by `split.ppp`) to be smoothed. Alternatively a list of point patterns, of class `"ppplist"`. `...` Arguments passed to `density.ppp` to control the smoothing, pixel resolution, edge correction etc. `se` Logical value indicating whether to compute standard errors as well.

## Details

This is a method for the generic function `density`.

The argument `x` should be a list of point patterns, and should belong to one of the classes `"ppplist"` or `"splitppp"`.

Typically `x` is obtained by applying the function `split.ppp` to a point pattern `y` by calling `split(y)`. This splits the points of `y` into several sub-patterns.

A kernel estimate of the intensity function of each of the point patterns is computed using `density.ppp`.

The return value is usually a list, each of whose entries is a pixel image (object of class `"im"`). The return value also belongs to the class `"solist"` and can be plotted or printed.

If the argument `at="points"` is given, the result is a list of numeric vectors giving the intensity values at the data points.

If `se=TRUE`, the result is a list with two elements named `estimate` and `SE`, each of the format described above.

## Value

A list of pixel images (objects of class `"im"`) which can be plotted or printed; or a list of numeric vectors giving the values at specified points.

If `se=TRUE`, the result is a list with two elements named `estimate` and `SE`, each of the format described above.

## Author(s)

and \rolf

`ppp.object`, `im.object`

## Examples

 ```1 2``` ``` Z <- density(split(amacrine), 0.05) plot(Z) ```

### Example output

```Loading required package: nlme