OneRun: Simulate Lotka-Volterra population dynamics and get summary...

In elsander/PredictImportance: Generate Networks, Simulate Abundance Data, and Analyze Importance Correlates

Description

Read in a matrix and population file, simulate discrete-time population dynamics with perturbed growth rates, and calculate species importance, variability, and degree. Note that this function is used internally, and many parameters (simtime, perturbation size) are hardcoded. Use discreteLV_C() for your own simulations or Step2_Discrete_LV() to replicate simulations from Wootton et al.

Usage

OneRun(matname, popname, immname, simtime = 1000, deltat = 0.001)

Arguments

matname	path to parameterized network to be simulated
popname	path to vector of equilibrium abundances for the network
immname	path to vector of immigration rates for species in the network
simtime	number of time steps to simulate
deltat	step size for simulation (smaller value will allow the model to more closely approximate a continuous-time Lotka-Volterra)

Value

a data frame containing Jaccard distance, perturbation importance, mean abundance, standard deviation of abundance over the simulation, and network degree for each species in the network.

elsander/PredictImportance documentation built on May 5, 2019, 3:49 a.m.