Kernel Smoothed Intensity of Split Point Pattern

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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

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  ## 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)

\adrian

and \rolf

See Also

ppp.object, im.object

Examples

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  Z <- density(split(amacrine), 0.05)
  plot(Z)

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