View source: R/simulateRicker.R
simulateRicker | R Documentation |
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.
simulateRicker(
n_species,
A,
names_species = NULL,
x0 = runif(n_species),
carrying_capacities = runif(n_species),
error_variance = 0.05,
explosion_bound = 10^8,
t_end = 1000,
norm = FALSE,
...
)
n_species |
Integer: number of species |
A |
interaction matrix |
names_species |
Character: names of species. If NULL,
|
x0 |
Numeric: initial abundances of simulated species. If NULL,
|
carrying_capacities |
numeric carrying capacities. If NULL,
|
error_variance |
Numeric: the variance of measurement error.
By default it equals to 0, indicating that the result won't contain any
measurement error. This value should be non-negative.
(default: |
explosion_bound |
numeric value of boundary for explosion
(default: |
t_end |
integer number of simulations to be simulated |
norm |
logical scalar returning normalised abundances (proportions
in each generation) (default: |
... |
additional parameters, see |
simulateRicker
returns a TreeSummarizedExperiment class object
Fisher & Mehta (2014). Identifying Keystone Species in the Human Gut Microbiome from Metagenomic Timeseries using Sparse Linear Regression. PLoS One 9:e102451
A <- powerlawA(10, alpha = 1.01)
tse <- simulateRicker(n_species = 10, A, t_end = 100)
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