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 splitppp
density(x, …, se=FALSE) # S3 method for ppplist
density(x, …, 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.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.
See Also
Examples
# NOT RUN {
Z <- density(split(amacrine), 0.05)
plot(Z)
# }