# rjitter

##### Random Perturbation of a Point Pattern

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

##### Usage

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

##### Arguments

- 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.

##### Details

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`

.

##### Value

- 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`

.

##### Examples

```
X <- rsyst(owin(), 10, 10)
Y <- rjitter(X, 0.02)
plot(Y)
Z <- rjitter(X)
```

*Documentation reproduced from package spatstat, version 1.41-1, License: GPL (>= 2)*