Applies independent random displacements to each point in a point pattern.
rjitter(X, ...)# S3 method for ppp
rjitter(X, radius, retry=TRUE, giveup = 10000, trim=FALSE,
..., nsim=1, drop=TRUE)
The result of rjitter.ppp is
a point pattern (an object of class "ppp")
or a list of point patterns.
A point pattern (object of class "ppp").
Scale of perturbations. A positive numerical value.
The displacement vectors will be uniformly
distributed in a circle of this radius.
There is a sensible default.
Alternatively, radius may be a numeric vector of length
equal to the number of points in X, giving a different
displacement radius for each data point.
What to do when a perturbed point lies outside the window
of the original point pattern. If retry=FALSE,
the point will be lost; if retry=TRUE,
the algorithm will try again.
Maximum number of unsuccessful attempts.
Logical value. If TRUE, the displacement radius
for each data point will be constrained to be less than or equal to
the distance from the data point to the window boundary.
This ensures that all displaced points will fall inside the window.
Ignored.
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.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner rolfturner@posteo.net and Ege Rubak rubak@math.aau.dk.
The function rjitter is generic, with methods for point
patterns (described here) and for some other types of geometrical objects.
Each of the points in the point pattern X is subjected to
an independent random displacement. The displacement vectors are
uniformly distributed in a circle of radius radius.
If a displaced point lies outside the window, then if
retry=FALSE the point will be lost.
However if retry=TRUE, the algorithm will try again: each time a
perturbed point lies outside the window, the algorithm will reject it and
generate another proposed perturbation of the original point,
until one lies inside the window, or until giveup unsuccessful
attempts have been made. In the latter case, any unresolved points
will be included without any perturbation. The return value will
always be a point pattern with the same number of points as X.
If trim=TRUE, then the displacement radius for each data point
will be constrained to be less than or equal to
the distance from the data point to the window boundary.
This ensures that the randomly displaced points will
always fall inside the window; no displaced points will be lost and no
retrying will be required.
rexplode
X <- rsyst(owin(), 10, 10)
Y <- rjitter(X, 0.02)
plot(Y)
Z <- rjitter(X)
U <- rjitter(X, 0.025, trim=TRUE)
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