crosstabm: create a contingency table between a comparison raster map...

crosstabmR Documentation

create a contingency table between a comparison raster map (rows) and a reference raster map (columns)

Description

create a contingency table, also called cross-tabulated matrix, between a comparison raster map (rows), or map at time t, and a reference raster map (columns), or map at time t+1

Usage

crosstabm(comp, ref, percent = FALSE, population = NULL)

Arguments

comp

object of class SpatRaster corresponding to the comparison map, or map at time t

ref

object of class SpatRaster corresponding to the reference map, or map at time t+1

percent

logical. If TRUE, output values are given as percentage. If FALSE, output values are given in pixel counts

population

an n x 2 matrix provided to correct the sample count to population count in the square contingency table. See Details below

Details

For correcting the sample count to population count in the square contingency table, assuming a stratified random sampling, an n (number of categories) by 2 matrix can be provided in the population argument. The first column of population must contains integer identifiers of each category, corresponding to the categories in the comparison map (or map at time t) and reference map (or map at time t+1). The second column corresponds to the population totals for each map category

Value

a matrix showing the cross-tabulation between the comparison map (or map at time t) and the reference map (or map at time t+1)

See Also

memberships

Examples

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

# Population-adjusted square contingency table
(population <- matrix(c(1, 2, 3, 2000, 4000, 6000), ncol = 2))
crosstabm(comp, ref, population = population)

# Population-adjusted square contingency table, output as percentage
crosstabm(comp, ref, percent = TRUE, population = population)

diffeR documentation built on Aug. 22, 2023, 9:11 a.m.