Diversity index

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Question

How to calculate diversity indices?

Answer

Upload your data to Opasnet Base. Use the function diversity to calculate the most common indices.

Actual function diversity

+ Show code- Hide code 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("S or 0D", "H' or log(1D)", "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) }

⇤--#: . With the example data, H' shows 0 which is not plausible. What's wrong? --Jouni 01:10, 5 January 2012 (EET) (type: truth; paradigms: science: attack)

Example to use function

Give your data in R format c(4,2,4,6,1,2,3,8,9) or leave empty for example data: Is your data individual data or group abundancies?: Individual Group + Show code- Hide code library(xtable) if(is.null(data)) {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 = individual) print(xtable(out), type = 'html')

Rationale

Diversity indices are thoroughly described in Wikipedia.

Related files

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