sta.mcoexistence: basic posterior coexistence analysis for a single scenario of...
In coexist: Species coexistence modeling and analysis

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

The basic statistic for multiple-species (>=2) coexistence simulation, which counts the coexistence of different species in the patches, gathers all the combinations of varying parameters. Its counterpart is sta.coexistence() function, which is used to handle a single scenario of 2-species simulation

1	sta.mcoexistence(outcome, island = 10, spnum)

`outcome`	A list of data for showing all species-site abundance matrices for each of all the combinations of varying parameters, just the direct output of fast.flexsim() or sim.coarse() functions. Alternatively, if the output of the simulation scenarios were stored in the local disk, you can use batch.read() or read.data() functions to get the data for sta.mcoexistence function
`island`	number of patches used in the modeling, default is 10
`spnum`	number of species considered (>=2)

This function will return a matrix, of columns from left to right are the countings of patch that have allowed the survival of only a single species (each of the total species number), then followed by the countings of patch that have allowed the coexistence of 2 species, 3 species,... until the column that all the species can coexist. After these columns, the others are values for each parameter combination.

Youhua Chen <yhchen@zoology.ubc.ca>

Chen YH (2012) coexist: an R package for performing species coexistence modeling and analysis under asymmetric dispersal and fluctuating source-sink dynamics. http://code.google.com/p/coexist.

sta.coexistence, batch.mcoexistence

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (outcome, island, spnum) 
{
    conum <- spnum * 2
    sta <- matrix(0, ncol = conum + length(outcome[[1]]$pars), 
        nrow = length(outcome))
    for (i in 1:length(outcome)) {
        for (j in 2:island) {
            num <- length(which(outcome[[i]]$abund[, j] != 0))
            if (num == 0) {
                sta[i, 1] = sta[i, 1] + 1
            }
            if (num == 1) {
                spindex <- which(outcome[[i]]$abund[, j] != 0)
                sta[i, spindex + 1] = sta[i, spindex + 1] + 1
            }
            if (num > 1) {
                sta[i, spnum + num] = sta[i, spnum + num] + 1
            }
        }
        sta[i, (conum + 1):dim(sta)[2]] = as.numeric(outcome[[i]]$pars)
    }
    colnames(sta) <- c(paste("s", c(0:spnum), sep = ""), paste("co", 
        c(2:spnum), sep = ""), names(outcome[[i]]$pars))
    return(sta)
  }