soi: Self-organized instable model

In hallucigenia-sparsa/seqtime: Time Series Analysis of Sequencing Data

Self-organized instable model

Description

Generate time series with the self-organized instable (SOI) model implementing model B by Sole et al. 2002. The model implements a K-leap method for accelerating stochastic simulation according to Cai et al. 2007

Usage

soi(N, I, A, m.vector = runif(N), e.vector = runif(N), tend, K = 5,
  perturb = NULL)

Arguments

N	number of species
I	number of individuals
A	interaction matrix
m.vector	species-specific immigration probabilities (these also determine initial abundances)
e.vector	species-specific extinction probabilities
tend	number of time points (i.e. the number of generations)
K	The parameter K gives the number of simulation events occurring during one leap. Cai et al. 2007 propose rules for the selection of K. However, as those rules may be considered conservative, K is a user-supplied parameter with a default of 5. A higher K gives a faster simulation, but is less accurate. Large values of K may also lead to errors caused by population abundances becoming negative, particularly if the extinction and immigration rates are high.
perturb	a perturbation object

Value

a matrix with species abundances as rows and time points as columns

References

Sole et al. Philos Trans R Soc Lond B Biol. Sci. "Self-organized instability in complex ecosystems" 357:667-671 (2002) Cai et al. The Journal of Chemical Physics "K-leap method for accelerating stochastic simulation of coupled chemical reactions" 126 (2007)

See Also

ricker for the Ricker model

Examples

## Not run: 
N=10
A=generateA(N,c=0.1)
tsplot(soi(N=N,I=1000,A=A,tend=100), header="SOI")

## End(Not run)

hallucigenia-sparsa/seqtime documentation built on Jan. 9, 2023, 11:53 p.m.