hab: Calculate Shannon diversity of all transitions.

In bjornbrooks/landat: R functions for calculating IT statistics

Description

Calculate measures of transition diversity using the Shannon index. Note that the formulas are conditional to omit zero probability values from the calculation.

Usage

hab(jd)

Arguments

jd	A matrix indicating the joint distribution across all interactions of X and Y in the form: p(x,y) Y 0.06 0.06 0.06 ... X 0.14 0.14 0.14 ... 0.12 0.12 0.14 ... ... ... ... ...

Details

Element-wise multiply matrix jd by logarithm base 2 jd and sum.

∑ -p(x_i,y_j) * log2 p(x_i,y_j) = -p(1,1) * log2 p(1,1) + -p(1,2) * log2 p(1,2) + … + -p(i,j) * log2 p(i,j)

Value

Returns a value indicating the Shannon diversity of all transitions.

Author(s)

Bjorn J. Brooks, Lars Y. Pomara, Danny C. Lee

References

PAPER TITLE.

Examples

data(transitions)             # Load example data
b <- brkpts(transitions$phenofr, # Find 10 probabilistically
            10)                  #  equivalent breakpoints
m <- xt(transitions,          # Make transition matrix
        fr.col=2, to.col=3,
        cnt.col=4, brk=b)
jd <- jpmf(m)                 # Joint distribution
hab(jd)                       # Shannon diversity

bjornbrooks/landat documentation built on May 17, 2019, 7:32 p.m.