prevalence | R Documentation |

Prevalence is the proportion of presences of a species in a dataset, which is required (together with presence probability) for computing `Fav`

ourability.

prevalence(obs, model = NULL, event = 1, na.rm = TRUE)

`obs` |
a vector or a factor of binary observations (e.g. 1 vs. 0, male vs. female, disease vs. no disease, etc.). This argument is ignored if 'model' is provided. |

`model` |
alternatively to 'obs', a binary-response model object of class "glm", "gam", "gbm", "randomForest" or "bart". If this argument is provided, 'obs' will be extracted with |

`event` |
the value whose prevalence we want to calculate (e.g. 1, "present", etc.). This argument is ignored if 'model' is provided. |

`na.rm` |
logical, whether NA values should be excluded from the calculation. The default is TRUE. |

Numeric value of the prevalence of `event`

in the `obs`

vector.

A. Marcia Barbosa

# calculate prevalence from binary vectors: (x <- rep(c(0, 1), each = 5)) (y <- c(rep(0, 3), rep(1, 7))) (z <- c(rep(0, 7), rep(1, 3))) prevalence(x) prevalence(y) prevalence(z) (w <- c(rep("yes", 3), rep("nope", 7))) prevalence(w, event = "yes") # calculate prevalence from a model object: data(rotif.env) mod <- glm(Abrigh ~ HabitatDiversity + HumanPopulation, family = binomial, data = rotif.env) prevalence(model = mod) # same as: prevalence(obs = rotif.env$Abrigh)

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