# prevalence: Prevalence In fuzzySim: Fuzzy Similarity in Species Distributions

 prevalence R Documentation

## Prevalence

### Description

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

### Usage

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

### Arguments

 `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 `mod2obspred`. `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.

### Value

Numeric value of the prevalence of `event` in the `obs` vector.

### Author(s)

A. Marcia Barbosa

### Examples

```
# 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)
```

fuzzySim documentation built on Oct. 31, 2022, 1:07 a.m.