The grouping variables. Default NULL
generates one output for all text. Also takes a single
grouping variable or a list of 1 or more grouping
variables.
Value
Returns a dataframe of various diversity related indices
for Shannon, collision, Berger Parker and Brillouin.
Details
These are the formulas used to calculate the indices:
Shannon index:
$$H_1(X)=-\sum\limits_{i=1}^R{p_i};log;p_i$$
Shannon, C. E. (1948). A mathematical theory of
communication. Bell System
Simpson index:
$$D=\frac{\sum_{i=1}^R{p_i};n_i(n_i -1)}{N(N-1))}$$
Simpson, E. H. (1949). Measurement of diversity. Nature
163, p. 688
Collision entropy:
$$H_2(X)=-log\sum_{i=1}^n{p_i}^2$$
Renyi, A. (1961). On measures of information and entropy.
Proceedings of the 4th Berkeley Symposium on Mathematics,
Statistics and Probability, 1960. pp. 547-5661.
Berger Parker index:
$$D_{BP}=\frac{N_{max}}{N}$$
Berger, W. H., & Parker, F. L.(1970). Diversity of
planktonic Foramenifera in deep sea sediments. Science
168, pp. 1345-1347.
Brillouin index:
$$H_B=\frac{ln(N!)-\sum{ln(n_1)!}}{N}$$
Magurran, A. E. (2004). Measuring biological diversity.
Blackwell.