# runifpoint

0th

Percentile

##### Generate N Uniform Random Points

Generate a random point pattern containing $n$ independent uniform random points.

Keywords
spatial, datagen
##### Usage
runifpoint(n, win=owin(c(0,1),c(0,1)), giveup=1000)
##### Arguments
n
Number of points.
win
Window in which to simulate the pattern. An object of class "owin" or something acceptable to as.owin.
giveup
Number of attempts in the rejection method after which the algorithm should stop trying to generate new points.
##### Details

This function generates n independent random points, uniformly distributed in the window win. (For nonuniform distributions, see rpoint.)

The algorithm depends on the type of window, as follows:

• Ifwinis a rectangle then$n$independent random points, uniformly distributed in the rectangle, are generated by assigning uniform random values to their cartesian coordinates.
• Ifwinis a binary image mask, then a random sequence of pixels is selected (usingsample) with equal probabilities. Then for each pixel in the sequence we generate a uniformly distributed random point in that pixel.
• Ifwinis a polygonal window, the algorithm uses the rejection method. It finds a rectangle enclosing the window, generates points in this rectangle, and tests whether they fall in the desired window. It gives up whengiveup * ntests have been performed without yieldingnsuccesses.
The algorithm for binary image masks is faster than the rejection method but involves discretisation.

##### Value

• The simulated point pattern (an object of class "ppp").

##### See Also

ppp.object, owin.object, rpoispp, rpoint

• runifpoint
##### Examples
# 100 random points in the unit square
pp <- runifpoint(100)
# irregular window
data(letterR)
# polygonal
pp <- runifpoint(100, letterR)
# binary image mask
pp <- runifpoint(100, as.mask(letterR))
Documentation reproduced from package spatstat, version 1.9-2, License: GPL version 2 or newer

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