# 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 to`as.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=1`

and`drop=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

```
X <- rstrat(nx=10)
plot(X)
# polygonal boundary
data(letterR)
X <- rstrat(letterR, 5, 10, k=3)
plot(X)
```

*Documentation reproduced from package spatstat, version 1.42-2, License: GPL (>= 2)*