Rout et al.'s (2009) "Declining" model

Equation 6 and others from Rout et al. 2009. Estimates a pre-extinction rate of decline, a Bayes factor comparing competing hypotheses of extinction / persistence, and a posterior probability that the species is extant at the end of the observation period.

Usage

RO09B1(records, pi = 0.5, n.chains = 4, n.iter = 110000, n.burnin = 10000)

Arguments

records: sighting records in cbin format (see convert_dodo for details).
pi: prior probability that \(H_0\) is true (defaults to \(\pi = 0.5\)).
n.chains: number of MCMC chains to run. Defaults to 4.
n.iter: number of iterations in each chain. Defaults to 110,000.
n.burnin: number of iterations to discard as burn-in. Defaults to 10,000.

Value

a list object with the original parameters and the rate of decline (\(a\)), the Bayes factor, and p(extant) included as elements.

Note

All sighting records are assumed to be certain and sampling effort is assumed to be constant. The Bayes Factor presented here is the inverse of the Bayes Factor as presented in the original paper, to allow for comparability with other models in this package (values > 1 imply extinction).

References

Key Reference

Rout, T. M., Salomon, Y., & McCarthy, M. A. (2009). Using sighting records to declare eradication of an invasive species. Journal of Applied Ecology, 46(1), 110-117. doi:10.1111/j.1365-2664.2008.01586.x

Other References

Solow, A. R. (1993). Inferring Extinction from Sighting Data. Ecology, 74(3), 962-964. doi:10.2307/1940821

Examples

if (FALSE) { # \dontrun{
# Run the bitterweed analysis from Rout et al. 2009
RO09B1(bitterweed)
# Run an example analysis using the Slender-billed Curlew data
RO09B1(curlew$cbin)
} # }