soi: Self-Organised Instability Model Community Simulation

In gheysenemma/microsimR: A Simulator Package with a collection of basic community models that outputs count data of microbial communities

Description

Generate time-series with the self-organised instability (SOI) model. Implements a K-leap method for accelerating stochastic simulation.

Usage

soi(
  N,
  I,
  A,
  migr_rates = runif(N, min = 0.1, max = 0.8),
  death_rates = runif(N, min = 0.01, max = 0.08),
  com = NULL,
  tend,
  k = 5,
  norm = FALSE
)

Arguments

N	number of species
I	community size, number of available sites (individuals)
A	interaction matrix of dimension NxN
migr_rates	species-specific immigration probabilities (also determine initial abundances)
death_rates	species-specific extinction probabilities
com	Initial community abundances vector. If NULL (default), based on migration rates.
tend	number of timepoints to be returned in the time series (nr of generations)
k	the number of transition events that are allowed to take place during one leap. By default set to 5. Higher values reduce runtime, but also accuracy of the simulation.
norm	logical to indicate whether the time series should be returned with the abundances as proportions (norm = TRUE) or the raw counts (norm = FALSE, default)

Value

matrix with species abundances as rows and time points as columns

Examples

soi(N = 10, I = 1000, A = powerlawA(n = 10, alpha = 1.2), tend = 150, norm = TRUE)

gheysenemma/microsimR documentation built on Dec. 20, 2021, 10:46 a.m.