unmarked (version 1.4.3)

goccu: Fit multi-scale occupancy models

Description

Fit multi-scale occupancy models as described in Nichols et al. (2008) to repeated presence-absence data collected using the robust design. This model allows for inference about occupancy, availability, and detection probability.

Usage

goccu(psiformula, phiformula, pformula, data, linkPsi = c("logit", "cloglog"),
      starts, method = "BFGS", se = TRUE, ...)

Value

An object of class unmarkedFitGOccu

Arguments

psiformula

Right-hand sided formula describing occupancy covariates

phiformula

Right-hand sided formula describing availability covariates

pformula

Right-hand sided formula for detection probability covariates

data

An object of class unmarkedFrameGOccu or unmarkedMultFrame

linkPsi

Link function for the occupancy model. Options are "logit" for the standard occupancy model or "cloglog" for the complimentary log-log link, which relates occupancy to site-level abundance.

starts

Starting values

method

Optimization method used by optim

se

Logical. Should standard errors be calculated?

...

Additional arguments to optim, such as lower and upper bounds

Author

Ken Kellner

Details

Primary periods could represent spatial or temporal sampling replicates. For example, you could have several spatial sub-units within each site, where each sub-unit was then sampled repeatedly. This is a frequent design for eDNA studies. Or, you could have multiple primary periods of sampling at each site (conducted at different times within a season), each of which contains several secondary sampling periods. In both cases the robust design structure can be used to estimate an availability probability in addition to detection probability. See Kery and Royle (2015) 10.10 for more details.

References

Kery, M., & Royle, J. A. (2015). Applied hierarchical modeling in ecology: Volume 1: Prelude and static models. Elsevier Science.

Nichols, J. D., Bailey, L. L., O'Connell Jr, A. F., Talancy, N. W., Campbell Grant, E. H., Gilbert, A. T., Annand E. M., Husband, T. P., & Hines, J. E. (2008). Multi-scale occupancy estimation and modelling using multiple detection methods. Journal of Applied Ecology, 45(5), 1321-1329.

See Also

occu, colext, unmarkedMultFrame, unmarkedFrameGOccu

Examples

set.seed(123)
M <- 100
T <- 5
J <- 4

psi <- 0.5
phi <- 0.3
p <- 0.4

z <- rbinom(M, 1, psi)
zmat <- matrix(z, nrow=M, ncol=T)

zz <- rbinom(M*T, 1, zmat*phi)
zz <- matrix(zz, nrow=M, ncol=T)

zzmat <- zz[,rep(1:T, each=J)]
y <- rbinom(M*T*J, 1, zzmat*p)
y <- matrix(y, M, J*T)
umf <- unmarkedMultFrame(y=y, numPrimary=T)

if (FALSE) {
  mod <- goccu(psiformula = ~1, phiformula = ~1, pformula = ~1, umf)
  plogis(coef(mod))
}