Applies independent random displacements to each point in a point pattern.

`rjitter(X, radius, retry=TRUE, giveup = 10000, …, nsim=1, drop=TRUE)`

X

A point pattern (object of class `"ppp"`

).

radius

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.

retry

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.

giveup

Maximum number of unsuccessful attempts.

…

Ignored.

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.

A point pattern (an object of class `"ppp"`

)
if `nsim=1`

, or a list of point patterns if `nsim > 1`

,
in the same window as `X`

.

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`

.

# NOT RUN { X <- rsyst(owin(), 10, 10) Y <- rjitter(X, 0.02) plot(Y) Z <- rjitter(X) # }