R: Simulation of presence-absence matrices (non-clustered)

randpop.nb {prabclus} | R Documentation

## Simulation of presence-absence matrices (non-clustered)

### Description

Generates a simulated matrix where the rows are interpreted as regions and the columns as species, 1 means that a species is present in the region and 0 means that the species is absent. Species are generated i.i.d.. Spatial autocorrelation of a species' presences is governed by the parameter `p.nb` and a list of neighbors for each region.

### Usage

    randpop.nb(neighbors, p.nb = 0.5, n.species, n.regions =
    length(neighbors), vector.species = rep(1, n.species),
    species.fixed = FALSE, pdf.regions = rep(1/n.regions, n.regions),
    count = TRUE, pdfnb = FALSE)

### Arguments

`neighbors` | A list with a component for every region. The components are vectors of integers indicating neighboring regions. A region without neighbors (e.g., an island) should be assigned a list `numeric(0)`.
`p.nb` | numerical between 0 and 1. The probability that a new region is drawn from the non-neighborhood of the previous regions belonging to a species under generation. Note that for a given presence-absence matrix, this parameter can be estimated by `autoconst` (called `pd` there).
`n.species` | integer. Number of species.
`n.regions` | integer. Number of regions.
`vector.species` | vector of integers. If `species.fixed=TRUE`, `vector.species` must have length `n.species` and gives the sizes (i.e., numbers of regions) of the species to generate. Else, the sizes are generated randomly from the empirical distribution of `vector.species`.
`species.fixed` | logical. See `vector.species`.
`pdf.regions` | numerical vector of length `n.species`. The entries must sum up to 1 and give probabilities for the regions to be drawn during the generation of a species. These probabilities are used conditional on the new region being a neighbor or a non-neighbor of the previous regions of the species, see `p.nb`.
`count` | logical. If `TRUE`, the number of the currently generated species is printed.
`pdfnb` | logical. If `TRUE`, the probabilities of the regions are modified according to the number of neighboring regions by dividing them relative to the others by min(1,number of neighbors).

### Details

The principle is that a single species with given size is generated one-by-one region. The first region is drawn according to `pdf.regions`. For all following regions, a neighbor or non-neighbor of the previous configuration is added (if possible), as explained in `pdf.regions`, `p.nb`.

### Value

A 0-1-matrix, rows are regions, columns are species.

### Author(s)

Christian Hennig chrish@stats.ucl.ac.uk http://www.homepages.ucl.ac.uk/~ucakche

### References

Hennig, C. and Hausdorf, B. (2004) Distance-based parametric bootstrap tests for clustering of species ranges. Computational Statistics and Data Analysis 45, 875-896. http://stat.ethz.ch/Research-Reports/110.html.

Hausdorf, B. and Hennig, C. (2003) Biotic Element Analysis in Biogeography. Systematic Biology 52, 717-723.

Hausdorf, B. and Hennig, C. (2003) Nestedness of nerth-west European land snail ranges as a consequence of differential immigration from Pleistocene glacial refuges. Oecologia 135, 102-109.

### See Also

`autoconst` estimates `p.nb` from matrices of class `prab`. These are generated by `prabinit`.

`prabtest` uses `randpop.nb` as a null model for tests of clustering. An alternative model is given by `cluspop.nb`.

### Examples

    data(nb)
    set.seed(2346)
    randpop.nb(nb, p.nb=0.1, n.species=5, vector.species=c(1,10,20,30,34))

[Package prabclus version 2.2-6 Index]