Simulation of presence-absence matrices (clustered)
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.
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)
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 |
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
|
n.species |
integer. Number of species. |
clus.specs |
integer not larger than |
reg.group |
vector of pairwise distinct integers not larger than
|
grouppf |
numerical. The probability of the region of
a clustered species to belong to the corresponding group of regions
is up-weighted by factor |
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 |
pdf.regions |
numerical vector of length |
count |
logical. If |
pdfnb |
logical. If |
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.
A 0-1-matrix, rows are regions, columns are species.
Hennig, C. and Hausdorf, B. (2004) Distance-based parametric bootstrap tests for clustering of species ranges. Computational Statistics and Data Analysis 45, 875-896.
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))
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