simJamil {coenocliner} | R Documentation |

## Simulate species abundance data following Jamil & ter Braak (2013)

### Description

Simulate species probability of occurrence data according
to the method used by Tahira Jamil and Cajo ter Braak in their recent
paper *Generalized linear mixed models can detect unimodal
species-environment relationships*.

### Usage

```
simJamil(
n,
m,
x,
gl = 4,
randx = TRUE,
tol = 0.5,
tau = gl/2,
randm = TRUE,
expectation = FALSE
)
```

### Arguments

`n` |
numeric; the number of samples/sites. |

`m` |
numeric, the number of species/variables. |

`x` |
numeric; values for the environmental gradient. Can be missing, in which case suitable values are generated. See Details. |

`gl` |
numeric; gradient length in arbitrary units. The default is 4 units with gradient values ranging from -2 to 2. |

`randx` |
logical; should locations along the gradient ( |

`tol` |
numeric; the species tolerances. Can be a vector of
length |

`tau` |
numeric; constant that ensures some of the optima are located beyond the observed gradient end points. |

`randm` |
logical; should species optima along the gradient be located randomly or equally-spaced? |

`expectation` |
logical; if |

### Value

a matrix of `n`

rows and `m`

columns containing the
simulated species abundance data.

### Author(s)

Gavin L. Simpson

### References

Jamil and ter Braak (2013) Generalized linear mixed models can detect unimodal species-environment relationships. *PeerJ* **1:e95**; DOI doi: 10.7717/peerj.95.

### Examples

```
set.seed(42)
N <- 100 # Number of locations on gradient (samples)
glen <- 4 # Gradient length
grad <- sort(runif(N, -glen/2, glen/2)) # sample locations
M <- 10 # Number of species
sim <- simJamil(n = N, m = M, x = grad, gl = glen, randx = FALSE,
randm = FALSE, expectation = TRUE)
## visualise the response curves
matplot(grad, sim, type = "l", lty = "solid")
## simulate binomial responses from those response curves
sim <- simJamil(n = N, m = M, x = grad, gl = glen, randx = FALSE,
randm = FALSE)
```

*coenocliner*version 0.2-3 Index]