prevalence: Prevalence

prevalenceR Documentation

Prevalence

Description

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

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.