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.
# S3 method for splitppp
density(x, ..., weights=NULL, se=FALSE) # S3 method for ppplist
density(x, ..., weights=NULL, se=FALSE)
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.
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.
The argument weights specifies numerical case weights
for the data points.
Normally it should be a list, with the same length as
x. The entry weights[[i]] will determine the
case weights for the pattern x[[i]], and may be given in
any format acceptable to density.ppp.
For example, weights[[i]] can be
a numeric vector of length equal to npoints(x[[i]]),
a single numeric value, a numeric matrix,
a pixel image (object of class "im"),
an expression, or a function of class "funxy".
For convenience, weights can also be a single expression,
or a single pixel image (object of class "im"),
or a single function of class "funxy".
ppp.object,
im.object
Z <- density(split(amacrine), 0.05)
plot(Z)
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