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Randomly allocates marks to a point pattern, or permutes the existing marks, or resamples from the existing marks.
rlabel(X, labels=marks(X), permute=TRUE, nsim=1, drop=TRUE)Point pattern (object of class "ppp",
"lpp", "pp3" or "ppx")
or line segment pattern (object of class "psp").
Vector of values from which the new marks will be drawn at random. Defaults to the vector of existing marks.
Logical value indicating whether to generate new marks
by randomly permuting labels or
by drawing a random sample with replacement.
Number of simulated realisations to be generated.
Logical. If nsim=1 and drop=TRUE (the default), the
result will be a point pattern, rather than a list
containing a point pattern.
If nsim = 1 and drop=TRUE,
a marked point pattern (of the same class as X).
If nsim > 1, a list of point patterns.
This very simple function allocates random marks to
an existing point pattern X. It is useful
for hypothesis testing purposes. (The function can also be applied
to line segment patterns.)
In the simplest case, the command rlabel(X) yields
a point pattern obtained from X by randomly permuting
the marks of the points.
If permute=TRUE, then labels should be a vector of
length equal to the number of points in X.
The result of rlabel will be a point pattern
with locations given by X and marks given by
a random permutation of labels (i.e. a random sample without
replacement).
If permute=FALSE, then labels may be a vector of
any length.
The result of rlabel will be a point pattern
with locations given by X and marks given by
a random sample from labels (with replacement).
marks<- to assign arbitrary marks.
# NOT RUN {
amacrine
# Randomly permute the marks "on" and "off"
# Result always has 142 "off" and 152 "on"
Y <- rlabel(amacrine)
# randomly allocate marks "on" and "off"
# with probabilities p(off) = 0.48, p(on) = 0.52
Y <- rlabel(amacrine, permute=FALSE)
# randomly allocate marks "A" and "B" with equal probability
data(cells)
Y <- rlabel(cells, labels=factor(c("A", "B")), permute=FALSE)
# }
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