rRandomLabeling: Simulations of a point pattern according to the null...

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/rRandomLabeling.R

Description

Simulates of a point pattern according to the null hypothesis of random labeling.

Usage

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rRandomLabeling(X, CheckArguments = TRUE)

Arguments

X

A weighted, marked, planar point pattern (wmppp.object).

CheckArguments

Logical; if TRUE, the function arguments are verified. Should be set to FALSE to save time in simulations for example, when the arguments have been checked elsewhere.

Details

Marks are redistributed randomly across the original point pattern.

Value

A new weighted, marked, planar point pattern (an object of class wmppp, see wmppp.object).

Author(s)

Eric Marcon <[email protected]>

References

Goreaud, F. et Pelissier, R. (2003). Avoiding misinterpretation of biotic interactions with the intertype K12 fonction: population independence vs random labelling hypotheses. Journal of Vegetation Science 14(5): 681-692.

See Also

rRandomLabelingM, rPopulationIndependenceK

Examples

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# Simulate a point pattern with five types
X <- rpoispp(50) 
PointType   <- sample(c("A", "B", "C", "D", "E"), X$n, replace=TRUE)
PointWeight <- runif(X$n, min=1, max=10)
X$marks <- data.frame(PointType, PointWeight)
X <- as.wmppp(X)

par(mfrow=c(2,2))
plot(X, main="Original pattern, Point Type", which.marks=2)
plot(X, main="Original pattern, Point Weight", which.marks=1)

# Randomize it
Y <- rRandomLabeling(X)
Z <- Y
# Types have been redistributed randomly across locations
plot(Y, main="Randomized pattern, Point Type", which.marks=2)
# weights too
Y <- Z
plot(Y, main="Randomized pattern, Point Weight", which.marks=1)

dbmss documentation built on March 19, 2018, 5:05 p.m.