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How to calculate diversity indices?
Upload your data to Opasnet Base. Use the function diversity to calculate the most common indices.
Actual function diversity
true <- function(pi, q){
qD <- (sum(pi^q))^(1 / (1 - q))
return(qD)
}
diversity <- function(data, individual = TRUE){
if(individual == FALSE) {pi <- data} else {
pi <- tapply(data, data, length)
pi <- pi/sum(pi)
}
out <- data.frame(Name = c("Richness", "Shannon index", "Simpson index", "Inverse Simpson index",
"Gini-Simpson index", "Berger-Parker index"),
Symbol = c("0D or S", "log(1D) or H'", "λ or 1/(2D)", "1/λ or 2D", "1-λ or 1-1/(2D)", "∞D"),
Value = c(true(pi,0), log(true(pi,1)), 1/true(pi,2), true(pi,2), 1-1/true(pi,2), max(pi)))
return(out)
}
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Example to use function
library(xtable) data <- c(1,4,6,9,3,4,5,6,5,4,3,3,5,5,7,5,5,4,3,4,5,6,8,9,5,4,5,4,3,3,4,9,6,6,4,5,3,2,1,1,2,3,4,3,2,3,4,5,6,7,7) out <- diversity(data, individual = TRUE) print(xtable(out), type = 'html') |
Diversity indices are thoroughly described in Wikipedia.
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