rlpp(n, f, ..., nsim=1, drop=TRUE)"linim")
or a function on a linear network (object of class "linfun").
Alternatively, f can be a list of functions or pixel images,
giving the densities of points of each type.
f if it is a function
or a list of functions.
nsim=1.
If drop=TRUE (the default), the result is a point pattern.
If drop=FALSE, the result is a list with one entry which is a
point pattern.
nsim = 1 and drop=TRUE,
a point pattern on the linear network,
i.e.\ an object of class "lpp".
Otherwise, a list of such point patterns.
L, on which the points will be generated,
is determined by the argument f.
If f is a function, it is converted to a pixel image
on the linear network, using any additional function arguments
.... If n is a single integer and f is a function or pixel image,
then independent random points are generated on L with
probability density proportional to f.
If n is an integer vector and f is a list of functions
or pixel images, where n and f have the same length,
then independent random points of several types are generated on
L, with n[i] points of type i having probability
density proportional to f[[i]].
runiflpp
g <- function(x, y, seg, tp) { exp(x + 3*y) }
f <- linfun(g, simplenet)
rlpp(20, f)
plot(rlpp(20, f, nsim=3))
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