# rthin

##### Random Thinning

Applies independent random thinning to a point pattern.

##### Usage

`rthin(X, P, ...)`

##### Arguments

- X
- A point pattern (object of class
`"ppp"`

) that will be thinned. - P
- Data giving the retention probabilities, i.e. the probability
that each point in
`X`

will be retained. Either a single number, or a vector of numbers, or a`function(x,y)`

, or a pixel image (object of class`"im"`

- ...
- Additional arguments passed to
`P`

, if it is a function.

##### Details

In a random thinning operation, each point of the pattern `X`

is randomly either deleted or retained (i.e. not deleted).
The result is a point pattern,
consisting of those points of `X`

that were retained.

Independent random thinning means that the retention/deletion of each point is independent of other points.

The argument `P`

determines the probability of **retaining**
each point. It may be
[object Object],[object Object],[object Object],[object Object]
If `P`

is a function, it should be `x,y`

and should yield a
numeric vector of the same length. The function may have extra
arguments which are passed through the `...`

argument.

##### Value

- A point pattern (object of class
`"ppp"`

).

##### Examples

```
data(redwood)
plot(redwood, main="thinning")
# delete 20\% of points
Y <- rthin(redwood, 0.8)
points(Y, col="green", cex=1.4)
# function
f <- function(x,y) { ifelse(x < 0.4, 1, 0.5) }
Y <- rthin(redwood, f)
# pixel image
Z <- as.im(f, redwood$window)
Y <- rthin(redwood, Z)
```

*Documentation reproduced from package spatstat, version 1.9-3, License: GPL version 2 or newer*