rPopulationIndependenceM {dbmss} | R Documentation |
Simulates of a point pattern according to the null hypothesis of population independence defined for M
rPopulationIndependenceM(X, ReferenceType, CheckArguments = TRUE)
X |
A weighted, marked, planar point pattern ( |
ReferenceType |
One of the point types. |
CheckArguments |
Logical; if |
Reference points are kept unchanged, other points are redistributed randomly across locations.
A new weighted, marked, planar point pattern (an object of class wmppp
, see wmppp.object
).
Marcon, E. and Puech, F. (2010). Measures of the Geographic Concentration of Industries: Improving Distance-Based Methods. Journal of Economic Geography 10(5): 745-762.
Marcon, E., F. Puech and S. Traissac (2012). Characterizing the relative spatial structure of point patterns. International Journal of Ecology 2012(Article ID 619281): 11.
rPopulationIndependenceK
, rRandomLabelingM
# 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(1,2))
plot(X, main="Original pattern, Point Type", which.marks=2)
# Randomize it
Y <- rPopulationIndependenceM(X, "A")
# Points of type "A" (circles) are unchanged,
# all other points have been redistributed randomly across locations
plot(Y, main="Randomized pattern, Point Type", which.marks=2)