Generate Artificial data under the GUILDS model

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

Thijs Janzen

Examples

generate.Guilds(theta = 200,
                alpha_x = 0.005,
                alpha_y = 0.001,
                J = 10000)
#> $guildX
#>  [1] 820 733 594 500 495 426 380 365 304 289 254 230 211 207 189 176 172 131 130
#> [20] 101  81  74  74  66  66  66  62  60  46  45  43  38  38  33  32  30  28  24
#> [39]  24  23  22  20  16  15  14  14  12  12  12  12  11  10   9   9   9   9   9
#> [58]   9   8   8   7   7   7   6   6   6   5   5   5   4   4   4   4   4   3   3
#> [77]   3   3   2   2   2   2   2   2   2   1   1   1   1   1   1   1   1   1   1
#> [96]   1   1   1
#> 
#> $guildY
#>  [1] 695 439 216 157  91  62  50  45  43  26  20  19  17  16  16  16  10   9   8
#> [20]   7   7   3   2   2   1   1   1   1   1   1   1   1   1   1   1
#>