unmarked (version 0.8-5)

occuRN: Fit the Occupancy model of Royle and Nichols...

Description

Fit the Occupancy model of Royle and Nichols

Usage

occuRN(formula, data, K=25, starts, method="BFGS", control=list(),
    se=TRUE)

Arguments

formula

double right-hand side formula describing covariates of detection and occupancy in that order.

data

unmarkedFrameOccu supplying data to the model.

K

the upper summation index used to numerically integrate out the latent abundance.

starts

initial values for the optimization.

method

Optimization method used by optim.

control

Other arguments passed to optim.

se

logical specifying whether or not to compute standard errors.

Value

• unmarkedFit object describing the model fit.

Details

See unmarked for detailed descriptions of passing data y, covdata.site, and covdata.obs, and specifying covariates with stateformula and detformula.

This function fits the latent abundance mixture model described in Royle and Nichols (2003).

The latent abundance of site $i$ is modelled as Poisson:

$$N_i \sim Poisson(\lambda_i)$$

The detection of a single individual in site $i$ during sample $j$ is modelled as Bernoulli:

$$w_{ij} \sim Bernoulli(r_{ij})$$.

Thus, the detection probability for a single site is linked to the detection probability for an individual by

$$p_{ij} = 1 - (1 - r_{ij}) ^ {N_i}$$

Covariates of $\lambda_i$ are modelled with the log link and covariates of $r_{ij}$ are modelled with the logit link.

References

Royle, J. A. and Nichols, J. D. (2003) Estimating Abundance from Repeated Presence-Absence Data or Point Counts. Ecology, 84(3) pp. 777--790.

Examples

data(birds)
woodthrushUMF <- unmarkedFrameOccu(woodthrush.bin)
(fm.wood.rn <- occuRN(~ obs ~ 1, woodthrushUMF))