generate.Guilds: Generate Artificial data under the GUILDS model

In GUILDS: Implementation of Sampling Formulas for the Unified Neutral Model of Biodiversity and Biogeography, with or without Guild Structure

Generate Artificial data under the GUILDS model

Description

Using this function it is possible to generate a community dataset consisting of two separate abundance vectors for each guild, where the data generated adhere to the Guilds model.

Usage

generate.Guilds(theta, alpha_x, alpha_y, J)

Arguments

theta	Fundamental Biodiversity Number theta
alpha_x	Dispersal Ability of Guild X
alpha_y	Dispersal Ability of Guild Y
J	Total number of individuals in the local community (e.g. J_X + J_Y).

Value

guildX	Vector containing the unlabeled abundances of species in Guild X
guildY	Vector containing the unlabeled abundances of species in Guild Y

Author(s)

Thijs Janzen

Examples

generate.Guilds(theta = 200,
                alpha_x = 0.005,
                alpha_y = 0.001,
                J = 10000)

GUILDS documentation built on Aug. 21, 2023, 5:10 p.m.