Calculates similarity-sensitive normalised subcommunity rho diversity (the
representativeness of subcommunity j). This measure may be calculated
for a series of orders, represented as a vector of qs.
norm_sub_rho(meta, qs)object of class metacommunity
vector of mode numeric containing q values
norm_sub_rho returns a standard output of class rdiv
R. Reeve, T. Leinster, C. Cobbold, J. Thompson, N. Brummitt, S. Mitchell, and L. Matthews. 2016. How to partition diversity. arXiv 1404.6520v3:1–9.
pop <- data.frame(a = c(1,3), b = c(1,1))
row.names(pop) <- paste0("sp", 1:2)
pop <- pop/sum(pop)
meta <- metacommunity(pop)
# Calculate normalised subcommunity rho diversity
norm_sub_rho(meta, 0:2)
#> measure q type_level type_name partition_level partition_name
#> 1 normalised rho 0 types subcommunity a
#> 2 normalised rho 0 types subcommunity b
#> 3 normalised rho 1 types subcommunity a
#> 4 normalised rho 1 types subcommunity b
#> 5 normalised rho 2 types subcommunity a
#> 6 normalised rho 2 types subcommunity b
#> diversity dat_id transformation normalised k max_d
#> 1 1.0000000 naive NA NA NA NA
#> 2 1.0000000 naive NA NA NA NA
#> 3 0.9837173 naive NA NA NA NA
#> 4 0.9428090 naive NA NA NA NA
#> 5 0.9696970 naive NA NA NA NA
#> 6 0.8888889 naive NA NA NA NA