randpop.nb {prabclus}

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 [e-mail] https://www.unibo.it/sitoweb/christian.hennig/en

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))