ricker: Generate time series with the Ricker model

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

Generate time series with the Ricker model

Description

The Ricker model is a discrete version of the generalized Lotka-Volterra model and is implemented here as proposed by Fisher and Mehta in PLoS ONE 2014.

Usage

ricker(N, A, K = rep(0.1, N), y = runif(N), sigma = 0.05,
  K.trend = NA, tend = 100, death.t = NA, tskip = 0,
  explosion.bound = 10^8, perturb = NULL)

Arguments

N	number of species
A	interaction matrix
K	a vector of carrying capacities
y	initial abundances
sigma	noise level, if set to a non-positive value, no noise is added
K.trend	a vector of positive or negative carrying capacity percentages specified between 0 and 1
tend	number of time points
death.t	species with abundance below this value are killed (abundance is set to 0)
tskip	number of initial time points to skip (to skip the transient)
explosion.bound	boundary for explosion
perturb	a perturbation object

Details

If an explosion occurs, -1 is returned. An explosion is reported if any species crosses the explosion bound. To avoid explosions, decrease the number of interactions in the interaction matrix and/or increase the number of negative interactions in the interaction matrix. K.trend contains carrying capacity percentages (from the original carrying capacity) that are added to each species' current carrying capacity in each time step. K.trend allows to simulate an environmental trend. Negative carrying capacities are set to zero. If both a perturbation and K.trend are specified, the perturbation is carried out first.

Value

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

References

Fisher & Mehta (2014). Identifying Keystone Species in the Human Gut Microbiome from Metagenomic Timeseries using Sparse Linear Regression. PLoS One 9:e102451

See Also

glv for the generalized Lotka Volterra model

Examples

tsplot(ricker(10,generateA(10),K=rep(0.01,10)),main="ricker")
per=perturbation(times=seq(10,100,10),durations=rep(1,10),numberchanges=c(0.1,rep(0,9)))
tsplot(ricker(10,generateA(10),K=rep(0.01,10),perturb=per))

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