rstrat
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.
Usage
rstrat(win=square(1), nx, ny=nx, k = 1, nsim=1, drop=TRUE)Arguments
- win
A window. An object of class
owin, or data in any format acceptable toas.owin().- nx
Number of tiles in each column.
- ny
Number of tiles in each row.
- k
Number of random points to generate in each tile.
- nsim
Number of simulated realisations to be generated.
- drop
Logical. If
nsim=1anddrop=TRUE(the default), the result will be a point pattern, rather than a list containing a point pattern.
Details
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 win:
if they do, they are deleted.
The result is a point pattern inside the window win.
This function is useful in creating dummy points for quadrature
schemes (see quadscheme) as well as in simulating
random point patterns.
Value
A point pattern (an object of class "ppp")
if nsim=1, or a list of point patterns if nsim > 1.
See Also
Examples
# NOT RUN {
X <- rstrat(nx=10)
plot(X)
# polygonal boundary
data(letterR)
X <- rstrat(letterR, 5, 10, k=3)
plot(X)
# }