R: Random Perturbation of a Point Pattern on a Network

rjitter.lpp {spatstat.linnet} | R Documentation

## Random Perturbation of a Point Pattern on a Network

### Description

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

### Usage

    ## S3 method for class 'lpp'
    rjitter(X, radius, ..., nsim = 1, drop = TRUE)

### Arguments

`X` | A point pattern on a linear network (object of class `"lpp"`).
`radius` | Scale of perturbations. A positive numerical value. Each point will be displaced by a random distance, with maximum displacement equal to this value.
`...` | 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

The function `rjitter` is generic. This function is the method for the class `"lpp"` of point patterns on a linear network.

Each of the points in `X` will be displaced along the network by a random amount, independently of other points. The maximum displacement distance is specified by `radius`. Each point remains on the same line segment of the network as it originally was.

### Value

A point pattern on a linear network (object of class `"lpp"`) or a list of such point patterns.

### Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk.

### See Also

`rjitter` for point patterns in two dimensions.

### Examples

       X <- runiflpp(3, simplenet)
       plot(X, pch=16)
       Y <- rjitter(X, 0.1)
       plot(Y, add=TRUE, cols=3)

[Package spatstat.linnet version 2.3-1 Index]