rcell
Simulate Baddeley-Silverman Cell Process
Generates a random point pattern, a simulated realisation of the Baddeley-Silverman cell process model.
Usage
rcell(win=square(1), nx=NULL, ny=nx, ..., dx=NULL, dy=dx,
N=10, nsim=1, drop=TRUE)
Arguments
- win
- A window.
An object of class
owin
, or data in any format acceptable toas.owin()
. - nx
- Number of columns of cells in the window.
Incompatible with
dx
. - ny
- Number of rows of cells in the window.
Incompatible with
dy
. - ...
- Ignored.
- dx
- Width of the cells. Incompatible with
nx
. - dy
- Height of the cells.
Incompatible with
ny
. - N
- Integer. Distributional parameter:
the maximum number of random points in each cell.
Passed to
rcellnumber
. - nsim
- Number of simulated realisations to be generated.
- drop
- Logical. If
nsim=1
anddrop=TRUE
(the default), the result will be a point pattern, rather than a list containing a point pattern.
Details
This function generates a simulated realisation of the
The tile width is determined
either by the number of columns nx
or by the
horizontal spacing dx
.
The tile height is determined
either by the number of rows ny
or by the
vertical spacing dy
.
The cell process is then generated in these tiles.
The random numbers of points are generated by rcellnumber
.
Some of the resulting random points may lie outside the window win
:
if they do, they are deleted.
The result is a point pattern inside the window win
.
Value
- A point pattern (an object of class
"ppp"
) ifnsim=1
, or a list of point patterns ifnsim > 1
.
References
Baddeley, A.J. and Silverman, B.W. (1984) A cautionary example on the use of second-order methods for analyzing point patterns. Biometrics 40, 1089-1094.
See Also
Examples
X <- rcell(nx=15)
plot(X)
plot(Kest(X))