# rthin

0th

Percentile

##### Random Thinning

Applies independent random thinning to a point pattern.

Keywords
spatial, datagen
##### 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 vectorised, that is, it should accept vector arguments 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").

• rthin
##### 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 1.11-8, License: GPL version 2 or newer

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