parredw: Parresol and Edwards' entropy.

Description Usage Arguments Details Value Examples

View source: R/oneill_leibovici_entropy.R

Description

Compute Parresol and Edwards' entropy, following Parresol and Edwards (2014), starting from data. References can be found at SpatEntropy.

Usage

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Arguments

data

A data matrix or vector, can be numeric, factor, character, ...

Details

This index is based on the transformed variable Z identifying couples of realizations of the variable of interest. A distance of interest is fixed: Parresol and Edwards' entropy is thought for areas sharing a border, as O'Neill's entropy. All contiguous couples of realizations of the variable of interest are counted and their relative frequencies are used to compute the index, which is the opposite of O'Neill's entropy. The function is able to work with grids containing missing data, specified as NA values. All NAs are ignored in the computation and only couples of non-NA observations are considered.

Value

a list of two elements:

Examples

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#numeric data, square grid
data=matrix(sample(1:5, 100, replace=TRUE), nrow=10)
parredw(data)
#plot data
plot(as.im(data, W=square(nrow(data))),
     col=gray(seq(1,0,l=length(unique(c(data))))),
     main="", ribbon=TRUE)

#character data, rectangular grid
data=matrix(sample(c("a","b","c"), 300, replace=TRUE), nrow=30)
parredw(data)
#plot data
plot(as.im(data, W=owin(xrange=c(0,ncol(data)), yrange=c(0,nrow(data)))),
     col=terrain.colors(length(unique(c(data)))),
     main="", ribbon=TRUE)

SpatEntropy documentation built on April 7, 2021, 5:09 p.m.