generate.Artificial.Data: Generate Artifical data that can be used by the STEPCAM model
In thijsjanzen/STEPCAM: ABC-SMC Inference of STEPCAM

Description Usage Arguments Value Author(s) Examples

View source: R/generateArtificialData.R

This function generates artifical data with a given number of species, traits and communities. The generated data can directly be used in STEPCAM-ABC inference.

1 2	generate.Artificial.Data(n_species, n_traits, n_communities, occurence_distribution, average_richness, sd_richness, mechanism_random)

`n_species`	The number of species in the species pool (so across all communities) of the desired dataset.
`n_traits`	The number of traits in the desired dataset.
`n_communities`	The number of communities in the desired dataset.
`occurence_distribution`	species occurrence distribution (analogous to species abundance distribution) in species pool. A lognormal distribution is assumed. The higher the value, the more uneven the occurrence distribution in the species pool
`average_richness`	average richness in local community as a proportion of richness in species pool
`sd_richness`	standard deviation in richness across communities
`mechanism_random`	if TRUE, species are randomly drawn from from species pool. If FALSE, it is assumed that a certain trait combination is optimal in each community and species with traits similar to this optimum more likely end up in the local community. Therefore, random.mechanism = FALSE assumes filtering processes to be most dominant in community assembly

`traits`	A matrix containing the traits for all species, rows are the different species, column correspond to the respective traits.
`abundances`	A matrix containing the abundances of all species for all plots. Rows correspond to species, columns to plots.

Fons van der Plas

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Artificial.Data <- generate.Artificial.Data(n_species=40, n_traits=3, n_communities = 5,
                   occurence_distribution = 0.2, average_richness = 0.5, sd_richness = 0.2,
                   mechanism_random = FALSE)