density.splitppp
Kernel Smoothed Intensity of Split Point Pattern
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
## S3 method for class 'splitppp':
density(x, \dots, se=FALSE) ## S3 method for class 'ppplist':
density(x, \dots, se=FALSE)
Arguments
- x
- Split point pattern (object of class
"splitppp"created bysplit.ppp) to be smoothed. Alternatively a list of point patterns, of class"ppplist". - ...
- Arguments passed to
density.pppto 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 namedestimateandSE, each of the format described above.
See Also
Examples
Z <- density(split(amacrine), 0.05)
plot(Z)