| scenariosFromStatistics | R Documentation |
The make.scenarios function requires prior knowledge of
population density and the intercept of the detection function
(g0). This function provides an alternative mechanism for generating
scenarios from a value of sigma and target values for the numbers of
individuals n and recaptures r. Only a halfnormal detection function
is supported (probability, not hazard), and many options in
make.scenarios have yet to be implemented. Only a single
detector layout and single mask may be specified.
scenariosFromStatistics(sigma, noccasions, traps, mask, nval, rval,
g0.int = c(0.001, 0.999))
sigma |
numeric vector of one or more values for sigma |
noccasions |
integer vector of number of sampling occasions |
traps |
traps object |
mask |
mask object |
nval |
integer vector of values of n |
rval |
integer vector of values of r |
g0.int |
numeric vector defining the interval to be searched for g0 |
The algorithm is based on R code in Appendix B of Efford, Dawson and Borchers (2009).
A scenario dataframe with one row for each combination of sigma,
noccasions, nval and rval.
Efford, M. G., Dawson, D. K. and Borchers, D. L. (2009) Population density estimated from locations of individuals on a passive detector array. Ecology 90, 2676–2682.
make.scenarios
grid36 <- make.grid(nx = 6, ny = 6, spacing = 200)
mask <- make.mask(grid36, buffer = 2000)
scen <- scenariosFromStatistics (sigma = c(200,400), noccasions = 44,
traps = grid36, mask = mask, nval = 14, rval = 34)
sim <- run.scenarios(scen, nrepl = 5, traps = grid36, mask = mask)
summary(sim)
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