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detect (version 0.4-0)

datocc: Simulated example for occupancy model

Description

Simulated example for occupancy model, see code below.

Usage

data(datocc)

Arguments

Format

A data frame with 1000 observations on the following 6 variables.
Y
true occupancy
W
observations
x1
random variables used as covariates
x2
random variables used as covariates
x3
random variables used as covariates
x4
random variables used as covariates
p.occ
probability of occurrence
p.det
probability of detection

Source

Simulated example.

Details

This simulated example corresponds to the ZI Binomial model implemented in the function svocc.

References

Lele, S.R., Moreno, M. and Bayne, E. (2011) Dealing with detection error in site occupancy surveys: What can we do with a single survey? Journal of Plant Ecology, 5(1), 22--31.

Examples

Run this code
data(datocc)
str(datocc)
## Not run: 
# ## simulation
# n <- 1000
# set.seed(1234)
# x1 <- runif(n, -1, 1)
# x2 <- as.factor(rbinom(n, 1, 0.5))
# x3 <- rnorm(n)
# x4 <- rnorm(n)
# beta <- c(0.6, 0.5)
# theta <- c(0.4, -0.5, 0.3)
# X <- model.matrix(~ x1)
# Z <- model.matrix(~ x1 + x3)
# mu <- drop(X %*% beta)
# nu <- drop(Z %*% theta)
# p.occ <- binomial("cloglog")$linkinv(mu)
# p.det <- binomial("logit")$linkinv(nu)
# Y <- rbinom(n, 1, p.occ)
# W <- rbinom(n, 1, Y * p.det)
# datocc <- data.frame(Y, W, x1, x2, x3, x4, p.occ, p.det)
# ## End(Not run)

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