Trap covariates in simulations

[stefano palmero]

Hi all,

I would like to include trap types (on/off road) in my SECRDESIGN scenarios but I am not sure how to do it.

First of all, trap types should be specified in the trap file.

When I know type-specific g0s, should I create two groups? Something like this:

## Scenarios
densities <- c(5e-05,1e-04,1.5e-04,2e-04)
g0 <- 0.01
sigmas <- c(3000,4000,5000)

scen <- make.scenarios(noccasions = c(60,80,100,120), nrepeats = 1,
                       D = densities * 0.75,
                       sigma = sigmas,
                       g0 = g0,
                       groups = c('on','off'))
off <- scen$group == 'off'
scen$g0[off] <- 0.02

and then of course g0~traptype etc...

But I am not sure about communication between trap file, scenarios and the model in this case

Thank you very much

Stefano

[Murray Efford]

Hi Stefano

Groups could work (examples at https://github.com/MurrayEfford/secr-simulations under STR). But there is a more direct way using explicit input of detector-specific detection parameters in sim.capthist. For a different reason (aiming to reduce number of occasions)  I started out with HHN instead of HN (hence lambda0 instead of g0), but this should also work with HN/g0. It's not pretty, but it seems to get there.

Murray

library(secrdesign)

# some detectors with a binary covariate 1,2
grid<- make.grid(8,8, spacing = 5000, detector = 'proximity')
onoff <- sample.int(2, nrow(grid), replace = TRUE)
covariates(grid) <- data.frame(onoff = onoff)
plot(secr::as.mask(grid), cov='onoff', dots = FALSE)

lambdas <- c(0.01,0.02)  # for covariate levels 1,2
sigmas  <- c(3000,4000,5000)

# manually construct some occasion x detector matrix inputs for sim.capthist

# (ultimately replaces lambda0, sigma from scen)
onedetpar <- function (noccasions, sigma) {
# filling by row re-uses detector-specific covariates on each occasion
mat <- matrix(lambdas[onoff], byrow = TRUE, nrow = noccasions, ncol = nrow(grid))
    list(detectpar = list(lambda0 = mat, sigma = sigma))
}

# all combinations of duration and sigma

dets <- expand.grid(noccasions = c(60,80,100,120), sigma = sigmas)
detarglist <- mapply(onedetpar, dets$noccasions, dets$sigma, SIMPLIFY = FALSE)

## Scenarios
densities <- c(5e-05,1e-04,1.5e-04,2e-04)

scen <- make.scenarios(
noccasions = 60,       # placeholder - replaced later

D          = densities * 0.75,

detectfn   = 'HHN',
lambda0    = 0.01,     # placeholder - replaced later
sigma      = 3000,     # placeholder - replaced later
detindex   = 1:12)

# force noccasions to follow matrices in detarg
scen$noccasions <- dets$noccasions[scen$detindex]

sims <- run.scenarios(
nrepl     = 20,
scenarios = scen,
trapset   = grid,
det.args  = detarglist,
fit       = TRUE,
fit.args  = list(detectfn = 'HHN', model = lambda0~onoff))

estimateSummary(sims)

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[stefano palmero]

Dear Murray,

Thank you very much for the help, as always.

I'll try this code out

Best

Stefano Palmero

Faculty of Environment and Natural Resources

University of Freiburg

Tennenbacher Straße 4

79106 Freiburg

Germany