simulateHubbellRates: Hubbell's neutral model simulation applied to time series

In microbiome/miaSim: Microbiome Data Simulation

Hubbell's neutral model simulation applied to time series

Description

Neutral species abundances simulation according to the Hubbell model. This model shows that losses in society can be replaced either by the birth of individuals or by immigration depending on their probabilities. The specific time between the events of birth or migration is calculated and time effect is considered to determine the next event.

Usage

simulateHubbellRates(
  n_species = NULL,
  x0 = NULL,
  names_species = NULL,
  migration_p = 0.01,
  metacommunity_probability = NULL,
  k_events = 1,
  growth_rates = NULL,
  error_variance = 0,
  norm = FALSE,
  t_end = 1000,
  ...
)

Arguments

n_species	Integer: number of species
x0	Numeric scalar. Indicates the initial species composition. If NULL, rep(100, n_species) is used.
names_species	Character: names of species. If NULL, paste0("sp", seq_len(n_species)) is used. (default: names_species = NULL)
migration_p	Numeric: the probability/frequency of migration from a metacommunity. (default: migration_p = 0.01)
metacommunity_probability	Numeric: Normalized probability distribution of the likelihood that species from the metacommunity can enter the community during the simulation. If NULL, rdirichlet(1, alpha = rep(1,n_species)) is used. (default: metacommunity_probability = NULL)
k_events	Integer scalar. Indicates the number of events to simulate before updating the sampling distributions. (Default: 1)
growth_rates	Numeric scalar. Indicates the maximum growth rates(mu) of species. If NULL, rep(1, n_species) is used. (Default: 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: error_variance = 0)
norm	Logical: whether the time series should be returned with the abundances as proportions (norm = TRUE) or the raw counts (default: norm = FALSE) (default: norm = FALSE)
t_end	Numeric: the end time of the simulationTimes, defining the modeled time length of the community. (default: t_end = 1000)
...	additional parameters, see utils to know more.

Value

simulateHubbellRates returns a TreeSummarizedExperiment class object

References

Rosindell, James et al. "The unified neutral theory of biodiversity and biogeography at age ten." Trends in ecology & evolution vol. 26,7 (2011).

Examples

set.seed(42)
tse <- simulateHubbellRates(n_species = 5)

miaViz::plotSeries(tse, x = "time")

# no migration, all stochastic birth and death
set.seed(42)
tse1 <- simulateHubbellRates(n_species = 5, migration_p = 0)

# all migration, no stochastic birth and death
set.seed(42)
tse2 <- simulateHubbellRates(
    n_species = 5,
    migration_p = 1,
    metacommunity_probability = c(0.1, 0.15, 0.2, 0.25, 0.3),
    t_end = 20,
    t_store = 200
)

# all migration, no stochastic birth and death, but with measurement errors
set.seed(42)
tse3 <- simulateHubbellRates(
    n_species = 5,
    migration_p = 1,
    metacommunity_probability = c(0.1, 0.15, 0.2, 0.25, 0.3),
    t_end = 20,
    t_store = 200,
    error_variance = 100
)

# model with specified inputs
set.seed(42)
tse4 <- simulateHubbellRates(
    n_species = 5,
    migration_p = 0.1,
    metacommunity_probability = c(0.1, 0.15, 0.2, 0.25, 0.3),
    t_end = 200,
    t_store = 1000,
    k_events = 5,
    growth_rates = c(1.1, 1.05, 1, 0.95, 0.9)
)

microbiome/miaSim documentation built on Oct. 25, 2024, 7:16 p.m.