parredw {SpatEntropy}

Parresol and Edwards' entropy.

Description

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

Usage

parredw(
  data,
  win = spatstat.geom::owin(xrange = c(0, ncol(data)), yrange = c(0, nrow(data))),
  plotout = T
)

Arguments

data

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

win

Optional, an object of class owin, the observation window for data plotting

plotout

Logical. Default to TRUE, produces an informative plot as part of the function output.

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 four elements:

• parredw Parresol and Edwards' entropy

• range the theoretical range of Parresol and Edwards' entropy, from -\log(I^2) to 0

• rel.parredw Parresol and Edwards' relative entropy (with the same interpretation as O'Neill's relative entropy)

• probabilities a table with absolute frequencies and estimated probabilities (relative frequencies) for all couple categories

Moreover, a plot of the dataset is produced.

Examples

#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=grDevices::gray(seq(1,0,length.out=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)