permutation.communities.a: Produces a set of random communities from a given matrix,...
In CNull: Fast Algorithms for Frequency-Preserving Null Models in Ecology

Description Usage Arguments Value Author(s) References See Also Examples

Given a matrix M and a number of repetitions k, the function produces k random communities based on the permutation model. This is equivalent to shuffling M according to this model as many as k times , each time outputing only a certain row (e.g. the top one) of the shuffled matrix. An alpha diversity measure f can be applied on the output communities to determine the null distribution of f for a row in M. This distribution is the same for every row of M. This is because the examined null model produces the same distribution for all rows of M; after shuffling M, each row has the same probability to store a specific community as any other in the resulting matrix.

1	permutation.communities.a(matrix, reps=1000)

`matrix`	A matrix with integer values. The matrix should not contain any NA values.
`reps`	The number of randomizations. This argument is optional and its default value is set to one thousand.

A matrix which stores communities generated based on the permutation model. Each row of the matrix corresponds to a different randomized community. The number of columns, and the names of the columns in the output matrix are the same as in the input matrix. The output matrix is not a shuffled version of the input matrix.

Constantinos Tsirogiannis (tsirogiannis.c@gmail.com)

Gotelli, N. J., 2000. Null Model Analysis of Species Co-Occurrence Patterns. Ecology, 81(9), pp.2606-2621.

Tsirogiannis, C., A. Kalvisa, B. Sandel and T. Conradi. Column-Shuffling Null Models Are Simpler Than You Thought. To appear.

permutation.random.values.a

require(CNull)

#Create a random integer matrix
comm = matrix(sample(1:300),nrow=15,ncol=20)

#Use permutation model to produce 2000 random communities 
permutation.communities.a(comm,reps=2000)