Simpson_r | R Documentation |
Simpson's entropy of the neighborhood of individuals, up to a distance \insertCiteShimatani2001SpatDiv.
Simpson_r(
spCommunity,
r = NULL,
spCorrection = "isotropic",
CheckArguments = TRUE
)
Simpson_rEnvelope(
spCommunity,
r = NULL,
NumberOfSimulations = 100,
Alpha = 0.05,
spCorrection = "isotropic",
SimulationType = "RandomLabeling",
Global = FALSE,
CheckArguments = TRUE
)
spCommunity |
A spatialized community (A wmppp.object with |
r |
A vector of distances. If |
spCorrection |
The edge-effect correction to apply when estimating the K function with Kest. Default is "isotropic". |
CheckArguments |
If |
NumberOfSimulations |
The number of simulations to run, 100 by default. |
Alpha |
The risk level, 5% by default. |
SimulationType |
A string describing the null hypothesis to simulate. The null hypothesis may be "RandomPosition": points are drawn in a Poisson process (default); "RandomLabeling": randomizes point types, keeping locations unchanged. |
Global |
Logical; if |
Simpson_r
returns an object of class fv
, see fv.object.
There are methods for print and plot for this class.
It contains the value of the spatially explicit Simpson's entropy for each distance in r
.
Simpson_rEnvelope
returns an envelope object envelope.
There are methods for print and plot for this class.
It contains the observed value of the function, its average simulated value and the confidence envelope.
# Generate a random community
spCommunity <- rSpCommunity(1, size=1000, S=3)
# Calculate the entropy and plot it
autoplot(Simpson_r(spCommunity))
# Generate a random community
spCommunity <- rSpCommunity(1, size=1000, S=3)
# Calculate the entropy and plot it
autoplot(Simpson_rEnvelope(spCommunity, NumberOfSimulations=10))
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