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diffTablej: calculates difference metrics at the category level from a...

Description Usage Arguments Value References See Also Examples

Description

calculates quantity, exchange and shift components of difference, as well as the overall difference, at the category level from a contingency table derived from the crosstabulation between a comparison variable (or variable at time t), and a reference variable (or variable at time t+1).

Quantity difference is defined as the amount of difference between the reference variable and a comparison variable that is due to the less than maximum match in the proportions of the categories. Exchange consists of a transition from category i to category j in some observations and a transition from category j to category i in an identical number of other observations. Shift refers to the difference remaining after subtracting quantity difference and exchange from the overall difference.

Usage

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diffTablej(ctmatrix)

Arguments

ctmatrix

matrix representing a square contingency table between a comparison variable (rows) and a reference variable (columns)

Value

data.frame containing difference metrics at the category level between a comparison variable (rows) and a reference variable (columns). Output values are given in the same units as ctmatrix

References

Pontius Jr., R.G., Millones, M. 2011. Death to Kappa: birth of quantity disagreement and allocation disagreement for accuracy assessment. International Journal of Remote Sensing 32 (15), 4407-4429.

Pontius Jr., R.G., Santacruz, A. 2014. Quantity, exchange and shift components of difference in a square contingency table. International Journal of Remote Sensing 35 (21), 7543-7554.

See Also

overallQtyD

Examples

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comp <- raster(system.file("external/comparison.rst", package="diffeR"))
ref <- raster(system.file("external/reference.rst", package="diffeR"))
ctmatCompRef <- crosstabm(comp, ref)
diffTablej(ctmatCompRef)

# Adjustment to population assumming a stratified random sampling
(population <- matrix(c(1,2,3,2000,4000,6000), ncol=2))
ctmatCompRef <- crosstabm(comp, ref, percent=TRUE, population = population)
diffTablej(ctmatCompRef)


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