## Usage

sim5(speciesData)

## Arguments

- speciesData
- binary presence-absence matrix
(rows = species, columns = sites).

## Value

Returns a binary presence-absence matrix with the same
dimensions and colsums as the input matrix.

## Description

Randomizes a binary matrix speciesData by reshuffling elements
within each column. Sampling weights for each row are proportional to
row sums. Makes a call to the vector_sample function.

## Details

This algorithm preserves differences among sites in species
richness, but assumes differences among species in commonness and rarity
are proportional to observed species occurrences (= row sums).

## Note

This algorithm preserves differences among sites in species richness
(= colsums), but assumes differences among species in commonness and rarity
are proportional to observed species occurrences (= rowsums). sim5 has a
high frequency of Type I errors with random matrices, so it is not
recommended for co-occurrence analysis.

## References

Gotelli, N.J. 2000. Null model analysis of species co-occurrence
patterns. Ecology 81: 2606-2621.

## Examples

randomMatrix <- sim5(speciesData = matrix(rbinom(40,1,0.5),nrow=8))