Description Usage Arguments Examples

Calculates overlap between models in environment space using latin hypercube sampling

1 2 | ```
env.overlap(model.1, model.2, env, tolerance = 0.001, max.reps = 10,
cor.method = "spearman", chunk.size = 1e+05)
``` |

`model.1` |
An enmtools.model object model object that can be projected using the predict() function |

`model.2` |
Another enmtools.model object or other model object that can be projected using the predict() function |

`env` |
A raster, raster stack of environmental data, or a list of minima and maxima for the environmental space to evaluate models over |

`tolerance` |
How close do successive overlap metrics have to be before we decide we're close enough to the final answer |

`max.reps` |
Maximum number of attempts that will be made to find suitable starting conditions |

`cor.method` |
Which method to use for calculating correlations between models |

`chunk.size` |
How many combinations of environmental variables to try at a time. If your niche breadth in environment space is small, increasing this value may help you get a result. |

1 2 3 4 5 6 7 | ```
data(iberolacerta.clade)
data(euro.worldclim)
cyreni <- iberolacerta.clade$species$cyreni
monticola <- iberolacerta.clade$species$monticola
cyreni.glm <- enmtools.glm(cyreni, euro.worldclim, f = pres ~ bio1 + bio12, nback = 500)
monticola.glm <- enmtools.glm(monticola, euro.worldclim, f = pres ~ bio1 + bio12, nback = 500)
env.overlap(cyreni.glm, monticola.glm, euro.worldclim)
``` |

danlwarren/ENMTools documentation built on Sept. 9, 2018, 4:23 p.m.

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