Description Usage Arguments Details Value Author(s)

Species distribution modeling with k-fold cross validation. Algorithms supported are "glm", "svm", "maxent", "mars", "rf", "cart.rpart" and "cart.tree"

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`kdata` |
Object returned by function leaveOneOut |

`data` |
Object returned by function biomat. 2D matrix with the dependent variable (presence/absence) in the first column and the independent variables in the rest (extracted from varstack) |

`algorithm` |
Any character of the following: |

`algorithm.args` |
Further arguments to be passed to the selected algorithm for modeling (functions involved are described in details) |

`weighting` |
Logical for model fitting with weighted presence/absences-s. Applicable for algorithms "glm", "mars", "rf" and "cart.rpart". Default is FALSE. |

`threshold` |
Cut value between 0 and 1 to calculate the confusion matrix. Default is 0.5. |

`tuneRF.args` |
list of arguments from function |

This function calculates the AUC with the function "auc" from package "PresenceAbsence". Package SDMTools must be detached.

A list with six components:

`model ` |
fitted model using all data for training |

`auc ` |
AUC statistic in the cross validation |

`kappa ` |
kappa statistic in the cross validation |

`tss ` |
true skill statistic in the cross validation |

`fold.models ` |
fitted model with partitioned data |

`ObsPred ` |
cross model prediction |

M. Iturbide

mopa documentation built on May 2, 2019, 6:47 a.m.

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