onpoint (version 1.0.6)

simulate_antecedent_conditions: simulate_antecedent_conditions

Description

Simulate heterogenous pattern

Usage

simulate_antecedent_conditions(x, i, j, nsim, heterogenous = FALSE, ...)

Value

list

Arguments

x

ppp

i

Mark of points that are not not changed.

j

Mark of points that are randomized.

nsim

Number of patterns to simulate.

heterogenous

If TRUE, points with the mark j are randomized using a heterogeneous Poisson process.

...

Arguments passed to spatstat.explore::density.ppp().

Details

Simulate point patterns as null model data for spatstat.explore::envelope() using antecedent conditions as null model. x must be a marked point pattern with two types of marks. Antecedent conditions are suitable as a null model if points of type i may influence points of type j, but not the other way around (Velazquez et al 2016). One example are the positions of seedlings that may be influenced by the position of mature trees.

Returns a list with ppp objects.

References

Velázquez, E., Martínez, I., Getzin, S., Moloney, K.A., Wiegand, T., 2016. An evaluation of the state of spatial point pattern analysis in ecology. Ecography 39, 1–14. <https://doi.org/10.1111/ecog.01579>

Wiegand, T., Moloney, K.A., 2014. Handbook of spatial point-pattern analysis in ecology. Chapman and Hall/CRC Press, Boca Raton, USA. <isbn:978-1-4200-8254-8>

See Also

envelope

Examples

set.seed(42)
pattern_a <- spatstat.random::runifpoint(n = 20)
spatstat.geom::marks(pattern_a) <- "a"
pattern_b <- spatstat.random::runifpoint(n = 100)
spatstat.geom::marks(pattern_b) <- "b"
pattern <- spatstat.geom::superimpose(pattern_a, pattern_b)

null_model <- simulate_antecedent_conditions(x = pattern, i = "a", j = "b", nsim = 19)
spatstat.explore::envelope(Y = pattern, fun = spatstat.explore::pcf,
nsim = 19, simulate = null_model)