# rthin

0th

Percentile

##### Random Thinning

Applies independent random thinning to a point pattern or segment pattern.

Keywords
manip, spatial, datagen
##### Usage
rthin(X, P, …, nsim=1, drop=TRUE)
##### Arguments
X

A point pattern (object of class "ppp" or "lpp" or "pp3" or "ppx") or line segment pattern (object of class "psp") that will be thinned.

P

Data giving the retention probabilities, i.e. the probability that each point or line in X will be retained. Either a single number, or a vector of numbers, or a function(x,y) in the R language, or a function object (class "funxy" or "linfun"), or a pixel image (object of class "im" or "linim").

Additional arguments passed to P, if it is a function.

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

In a random thinning operation, each point of the point 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

a single number,

so that each point will be retained with the same probability P;

a vector of numbers,

so that the ith point of X will be retained with probability P[i];

a function P(x,y),

so that a point at a location (x,y) will be retained with probability P(x,y);

an object of class "funxy" or "linfun",

so that points in the pattern X will be retained with probabilities P(X);

a pixel image,

containing values of the retention probability for all locations in a region encompassing the point pattern.

If P is a function P(x,y), 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

An object of the same kind as X if nsim=1, or a list of such objects if nsim > 1.

##### Reproducibility

The algorithm for random thinning was changed in spatstat version 1.42-3. Set spatstat.options(fastthin=FALSE) to use the previous, slower algorithm, if it is desired to reproduce results obtained with earlier versions.

• rthin
##### Examples
# NOT RUN {
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, Window(redwood))
Y <- rthin(redwood, Z)

# pattern on a linear network
A <- runiflpp(30, simplenet)
B <- rthin(A, 0.2)
g <- function(x,y,seg,tp) { ifelse(y < 0.4, 1, 0.5) }
B <- rthin(A, linfun(g, simplenet))

# thin other kinds of patterns
E <- rthin(osteo$pts[[1]], 0.6) L <- rthin(copper$Lines, 0.5)
# }

Documentation reproduced from package spatstat, version 1.63-3, License: GPL (>= 2)

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