Simulate Stratified Random Point Pattern
Generates a ``stratified random'' pattern of points in a window,
by dividing the window into rectangular tiles and placing
k random points independently in each tile.
rstrat(win=square(1), nx, ny=nx, k = 1, nsim=1, drop=TRUE)
- A window.
An object of class
owin, or data in any format acceptable to
- Number of tiles in each column.
- Number of tiles in each row.
- Number of random points to generate in each tile.
- Number of simulated realisations to be generated.
- Logical. If
drop=TRUE(the default), the result will be a point pattern, rather than a list containing a point pattern.
This function generates a random pattern of points in a ``stratified random'' sampling design. It can be useful for generating random spatial sampling points.
The bounding rectangle of
win is divided into
a regular $nx \times ny$ grid of rectangular tiles.
In each tile,
k random points are generated independently
with a uniform distribution in that tile.
Some of these grid points may lie outside the window
if they do, they are deleted.
The result is a point pattern inside the window
This function is useful in creating dummy points for quadrature
quadscheme) as well as in simulating
random point patterns.
- A point pattern (an object of class
nsim=1, or a list of point patterns if
nsim > 1.
X <- rstrat(nx=10) plot(X) # polygonal boundary data(letterR) X <- rstrat(letterR, 5, 10, k=3) plot(X)