R/functional.beta.multi.R

In betapart: Partitioning Beta Diversity into Turnover and Nestedness Components

functional.beta.multi<-function (x, traits, index.family = "sorensen", warning.time=TRUE) 
{
    index.family <- match.arg(index.family, c("jaccard", "sorensen"))
    fbc<-x
    if (!inherits(x, "functional.betapart")) {
        fbc <- functional.betapart.core(x,traits, multi=TRUE, warning.time=warning.time, return.details=FALSE)
    } # end of computing core results
    
    maxbibj <- sum(fbc$max.not.shared[lower.tri(fbc$max.not.shared)])
    
    minbibj <- sum(fbc$min.not.shared[lower.tri(fbc$min.not.shared)])
    
    
    switch(index.family, sorensen = {
        funct.beta.sim <- minbibj/(minbibj + fbc$a)
        
        funct.beta.sne <- (fbc$a/(minbibj + fbc$a)) * ((maxbibj - minbibj)/((2 * fbc$a) + maxbibj + minbibj))
        
        funct.beta.sor <- (minbibj + maxbibj)/(minbibj + maxbibj +  (2 * fbc$a))
        
        functional.multi <- list(funct.beta.SIM = funct.beta.sim, funct.beta.SNE = funct.beta.sne,  funct.beta.SOR = funct.beta.sor)
    								}, 
    
    
    jaccard = {
        funct.beta.jtu <- (2 * minbibj)/((2 * minbibj) + fbc$a)
        
        funct.beta.jne <- (fbc$a/((2 * minbibj) + fbc$a)) * ((maxbibj - minbibj)/((fbc$a) + maxbibj + minbibj))
        
        funct.beta.jac <- (minbibj + maxbibj)/(minbibj + maxbibj + fbc$a)
        
        functional.multi <- list(funct.beta.JTU = funct.beta.jtu, funct.beta.JNE = funct.beta.jne, funct.beta.JAC = funct.beta.jac)
    			}
    
    ) # end of switch
    
    return(functional.multi)
    
} # end of function