cluspop.nb {prabclus}

Simulation of presence-absence matrices (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 in order to produce 2 clusters of species with similar ranges. Spatial autocorrelation of a species' presences is governed by the parameter p.nb and a list of neighbors for each region.

Usage

cluspop.nb(neighbors, p.nb = 0.5, n.species, clus.specs, reg.group,
grouppf = 10, n.regions = length(neighbors),
vector.species = rep(1, n.species), 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.

clus.specs

integer not larger than n.species. Number of species restricted to one of the two groups of regions defined by reg.group (called "clustered species" because this leads to more similar species ranges).

reg.group

vector of pairwise distinct integers not larger than n. regions. Defines a group of regions to which a part of the clus.specs clustered species is restricted (more or less, see grouppf). The other clustered species are restricted to the complementary regions.

grouppf

numerical. The probability of the region of a clustered species to belong to the corresponding group of regions is up-weighted by factor grouppf compared to the generation of "non-clustered" species.

n.regions

integer. Number of regions.

vector.species

vector of integers. The sizes (i.e., numbers of regions) of the species are generated randomly from the empirical distribution of 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, modified by grouppf for the clustered species.

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 non-clustered species are generated as explained on the help page for randpop.nb. The general principle for the clustered species is the same, but with modified probabilities for the regions. For each clustered species, one of the two groups of regions is drawn, distributed according to the sum of its regions' probability given by pdf.regions. The first region of such a species is only drawn from the regions of this group.

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.

See Also

randpop.nb,

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

Examples

data(nb)
set.seed(888)
cluspop.nb(nb, p.nb=0.1, n.species=10, clus.specs=9, reg.group=1:17,
vector.species=c(10))