coexist (version 1.0)

sta.paircomparison: pairwise parameter comparison for 2-species model

Description

explore coexistence patch number/density for a single scenario of a pair of parameters, for the case of 2-species modeling

Usage

sta.paircomparison(coexistence, parnum, parameters)

Arguments

coexistence

list of data generated by sta.coexistence() function

parnum

number of parameters you want to choose and compare pairwisely in the model, should be less than the total number of parameters i.e.,, for two species model

parameters

a parameter sampling point vector,for example parameters=c(.2,.5,.9), indicating three sampling points in a single parameter. The function will thus compare the coexistence patch numbers under the cases when each of the pairwise parameters (for example, growth rate and the competition ability of a species)=0.2,0.5 and 0.9 respectively.

References

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.

See Also

sta.paircomparison, sta.coexistence, batch.paircomp

Examples

##---- 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 (coexistence, parnum = parnum, parameters = parspace) 
{
    comparisonlist <- list()
    length(comparisonlist) <- parnum * (parnum - 1)/2
    varlist <- comparisonlist
    namesvector <- vector()
    length(namesvector) <- length(comparisonlist)
    count = 0
    for (p1 in 1:(parnum - 1)) {
        for (p2 in (p1 + 1):parnum) {
            conum <- matrix(0, ncol = length(parameters), nrow = length(parameters))
            varmat <- conum
            count = count + 1
            for (i in 1:length(parameters)) {
                for (j in 1:length(parameters)) {
                  temp <- coexistence[which(coexistence[, 3 + 
                    p1] == parameters[i] & coexistence[, 3 + 
                    p2] == parameters[j]), ]
                  conum[i, j] <- mean(temp[, 3])
                  varmat[i, j] <- var(temp[, 3])
                }
            }
            comparisonlist[[count]] <- conum
            namesvector[count] <- paste(colnames(coexistence)[3 + 
                p1], colnames(coexistence)[3 + p2], sep = "-")
            varlist[[count]] <- varmat
        }
    }
    names(comparisonlist) <- namesvector
    names(varlist) <- namesvector
    return(list(mean = comparisonlist, var = varlist))
  }