SIBER: generateSiberCommunity – R documentation

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generateSiberCommunity

A utility function to simulate a single community comprised of groups

Description

This function simulates data for a single community by sampling from a normal distribution with different means for each group within some specified boundaries.

Usage

generateSiberCommunity(
  n.groups = 3,
  community.id = 1,
  n.obs = 30,
  mu.range = c(-1, 1, -1, 1),
  wishSigmaScale = 1
)

Arguments

`n.groups`	the an integer specifying the number of groups to simulate. Defaults to 3.
`community.id`	an integer identifying the community's ID number. Defaults to 1.
`n.obs`	the number of observations to draw per group.
`mu.range`	a vector of length 4, specifying the mix and max x and y values to sample means from. Group means are sampled from a uniform distribution within this range. The first two entries are the min and max of the x-axis, and the second two the min and max of the y-axis. Defaults to `c(-1, 1, -1, 1)`.
`wishSigmaScale`	is a simple multiplier for the call to `rWishart` which scales the diagonal sigma matrix using `wishSigmaScale * diag(2)` that is ultimately passed on to `generateSiberGroup`.

Value

A data.frame object comprising a column of x and y data, a group identifying column and a community identifying column, all of which are numeric.

SIBER

Stable Isotope Bayesian Ellipses in R

v2.1.6

GPL (>= 2)

Authors

Andrew Jackson and Andrew Parnell

Initial release