Creates null matrices based on the constraints of the null model algorithm ('method'). Also allows for null matrices with a species that occurs at no sites, or a site without any species to be removed from the suite of simulated null matrices. This function borrows heavily from the commsimulator() function in the 'vegan' package, but also allows for the fixed-fixed null model.
NullMaker(comm, sims = 1000, method = "r1", ordinate = FALSE,
scores = 1, allowEmpty = FALSE, verbose = FALSE, seed = 1)community data in the form of a presence absence matrix
number of simulated null matrices to use in analysis
null model randomization method. See details below.
logical. Would you like to ordinate the null matrices? Default is FALSE.
Axis scores to ordinate matrix. 1: primary axis scores (default) 2: secondary axis scores. See Details.
logical argument indicating whether to allow null matrices to have empty rows or columns
Logical. Prints a graphical progress bar that tracks the creation of null matrices. Useful for conservative null models on large and/or sparse data.
seed for simulating the null model. Null matrices should be repeatable.
rmats -- A list of length(sim) containing the null matrices
'method' is the null model algorithm used to create the null matrices. The choice of a null algorithm is nontrivial. Leibold & Mikkelson advocated the use of equiprobable rows and columns (provided that rows and columns had at least one entry). This method is called 'r00'. Methods maintaining row (site) frequencies include 'r0','r1' & 'r2', whereas species (column) occurrences are preserved with fixed column methods such as 'c0'. The default method argument is 'r1', which maintains the species richness of a site (row totals) and fills species ranges (columns) based on their marginal probabilities. Arguably the most conservative null algorithm is the fixed row - fixed column total null, which can be attained using many of swap algorithms described in the vegan package (sequential methods like 'tswap', 'swap', and non-sequential 'quasiswap' and 'backtracking'). Other randomization methods are also available. See the help file for 'commsim', or Wright et al. 1998 for more information.
J. Oksanen, F.G. Blanchet, R. Kindt, P. Legendre, P.R. Minchin, R.B. O'Hara, G.L. Simpson, P. Solymos, M.H.H. Stevens and H. Wagner (2012). vegan: Community Ecology Package. R package version 2.0-4. http://CRAN.R-project.org/package=vegan
nullmodel(), permatfull(), commsim()
# NOT RUN {
#define an interaction matrix
data(TestMatrices)
intmat <- TestMatrices[[7]]
#creation of the null matrices
nulls <- NullMaker(intmat, sims=100, method='r1')
# }
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