R: Random Re-Labelling of Point Pattern

rlabel {spatstat.random} | R Documentation

## Random Re-Labelling of Point Pattern

### Description

Randomly allocates marks to a point pattern, or permutes the existing marks, or resamples from the existing marks.

### Usage

       rlabel(X, labels=marks(X), permute=TRUE, group=NULL, ..., nsim=1, drop=TRUE)

### Arguments

`X` | Point pattern (object of class `"ppp"`, `"lpp"`, `"pp3"` or `"ppx"`) or line segment pattern (object of class `"psp"`).
`labels` | Vector of values from which the new marks will be drawn at random. Defaults to the vector of existing marks.
`permute` | Logical value indicating whether to generate new marks by randomly permuting `labels` or by drawing a random sample with replacement.
`group` | Optional. A factor, or other data dividing the points into groups. Random relabelling will be performed separately within each group. See Details.
`...` | Additional arguments passed to `cut.ppp` to determine the grouping factor, when `group` is given.
`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

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).

The argument `group` specifies that the points are divided into several different groups, and that the random labelling shall be performed separately on each group. The arguments `group` and `...` are passed to `cut.ppp` to determine the grouping. Thus `group` could be a `factor`, or the name of a column of marks in `X`, or a tessellation, or a factor-valued pixel image, etc.

### Value

If `nsim = 1` and `drop=TRUE`, a marked point pattern (of the same class as `X`). If `nsim > 1`, a list of 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

`marks<-` to assign arbitrary marks.

### Examples

       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
       Y <- rlabel(cells, labels=factor(c("A", "B")), permute=FALSE)

       # divide the window into tiles and
       # randomly permute the marks within each tile
       Z <- rlabel(amacrine, group=quadrats(Window(amacrine), 4, 3))

[Package spatstat.random version 2.1-0 Index]