SADISA_sim: Simulates species abundance data

Description Usage Arguments Details Value References

View source: R/SADISA_sim.R

Description

Simulates species abundance data using the independent-species approach

Usage

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SADISA_sim(parsmc, ii, jj, model = c("pm", "dl"), mult = "single",
  nsim = 1)

Arguments

parsmc

The model parameters. For the point mutation (pm) model this is theta and I. For the protracted model (pr) this is theta, phi and I. For the density-dependent model (dd) - which can also be interpreted as the per-species speciation model, this is theta and alpha.

ii

The I parameter. When I is a vector, it is assumed that each value describes a sample or a guild depending on whether mult == 'ms' or mult == 'mg'. When mult = 'both', a list of lists must be specified, with each list element relates to a sample and contains a list of values across guilds.

jj

the sample sizes for each sample and each guild. Must have the same structure as ii

model

the chosen combination of metacommunity model and local community model as a vector, e.g. c('pm','dl') for a model with point mutation in the metacommunity and dispersal limitation. The choices for the metacommunity model are: 'pm' (point mutation), 'rf' (random fission), 'pr' (protracted speciation), 'dd' (density-dependence). The choices for the local community model are: 'dl' (dispersal limitation), 'dd' (density-dependence).

mult

When set to 'single', the loglikelihood of a single abundance vector will be computed When set to 'mg' the loglikelihood for multiple guilds is computed. When set to 'ms' the loglikelihood for multiple samples from the same metacommunity is computed. When set to 'both' the loglikelihood for multiple guilds within multiple samples is computed.

nsim

Number of simulations to perform

Details

Not all combinations of metacommunity model and local community model have been implemented yet. because this requires checking for numerical stability of the integration. The currently available model combinations are c('pm','dl').

Value

abund abundance vector, a list of abundance vectors, or a list of lists of abundance vectors, or a list of lists of lists of abundance vectors The first layer of the lists corresponds to different simulations When mult = 'mg', each list contains a list of abundance vectors for different guilds. When mult = 'ms', each list contains a list of abundance vectors for different samples from the same metacommunity. In this case the vectors should have equal lengths and may contain zeros because there may be species that occur in multiple samples and species that do not occur in some of the samples. When mult = 'both', each list will be a list of lists of multiple guilds within a sample

References

Haegeman, B. & R.S. Etienne (2017). A general sampling formula for community structure data. Methods in Ecology & Evolution 8: 1506-1519. doi: 10.1111/2041-210X.12807


SADISA documentation built on Oct. 30, 2019, 10:25 a.m.